Overview

Brought to you by YData

Dataset statistics

Number of variables223
Number of observations584201
Missing cells87470577
Missing cells (%)67.1%
Total size in memory982.2 MiB
Average record size in memory1.7 KiB

Variable types

Numeric23
Unsupported125
Text71
Boolean4

Dataset

DescriptionHerpetology NMNH Extant Specimen Records 0054921-241126133413365
URLhttps://doi.org/10.15468/dl.rf2che

Alerts

license has constant value "CC0_1_0" Constant
publisher has constant value "National Museum of Natural History, Smithsonian Institution" Constant
institutionID has constant value "urn:lsid:biocol.org:col:34871" Constant
collectionID has constant value "urn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0" Constant
institutionCode has constant value "USNM" Constant
collectionCode has constant value "HERP" Constant
datasetName has constant value "NMNH Extant Biology" Constant
occurrenceStatus has constant value "PRESENT" Constant
kingdom has constant value "Animalia" Constant
phylum has constant value "Chordata" Constant
datasetKey has constant value "821cc27a-e3bb-4bc5-ac34-89ada245069d" Constant
publishingCountry has constant value "US" Constant
kingdomKey has constant value "1" Constant
phylumKey has constant value "44.0" Constant
protocol has constant value "EML" Constant
lastCrawled has constant value "2024-12-02T11:48:23.416Z" Constant
publishedByGbifRegion has constant value "NORTH_AMERICA" Constant
hasGeospatialIssues is highly imbalanced (96.4%) Imbalance
isSequenced is highly imbalanced (98.6%) Imbalance
accessRights has 584201 (100.0%) missing values Missing
bibliographicCitation has 584201 (100.0%) missing values Missing
language has 584201 (100.0%) missing values Missing
references has 584201 (100.0%) missing values Missing
rightsHolder has 584201 (100.0%) missing values Missing
type has 584201 (100.0%) missing values Missing
datasetID has 584201 (100.0%) missing values Missing
ownerInstitutionCode has 584201 (100.0%) missing values Missing
informationWithheld has 584201 (100.0%) missing values Missing
dataGeneralizations has 584201 (100.0%) missing values Missing
dynamicProperties has 584201 (100.0%) missing values Missing
recordNumber has 583925 (> 99.9%) missing values Missing
recordedBy has 584201 (100.0%) missing values Missing
recordedByID has 584201 (100.0%) missing values Missing
organismQuantity has 584201 (100.0%) missing values Missing
organismQuantityType has 584201 (100.0%) missing values Missing
sex has 531942 (91.1%) missing values Missing
lifeStage has 542754 (92.9%) missing values Missing
reproductiveCondition has 584201 (100.0%) missing values Missing
caste has 584201 (100.0%) missing values Missing
behavior has 584201 (100.0%) missing values Missing
vitality has 584201 (100.0%) missing values Missing
establishmentMeans has 584201 (100.0%) missing values Missing
degreeOfEstablishment has 584201 (100.0%) missing values Missing
pathway has 584201 (100.0%) missing values Missing
georeferenceVerificationStatus has 584201 (100.0%) missing values Missing
disposition has 584201 (100.0%) missing values Missing
associatedOccurrences has 584201 (100.0%) missing values Missing
associatedReferences has 584201 (100.0%) missing values Missing
associatedSequences has 583480 (99.9%) missing values Missing
associatedTaxa has 584201 (100.0%) missing values Missing
otherCatalogNumbers has 584201 (100.0%) missing values Missing
occurrenceRemarks has 557618 (95.4%) missing values Missing
organismID has 584201 (100.0%) missing values Missing
organismName has 584201 (100.0%) missing values Missing
organismScope has 584201 (100.0%) missing values Missing
associatedOrganisms has 584201 (100.0%) missing values Missing
previousIdentifications has 584201 (100.0%) missing values Missing
organismRemarks has 584201 (100.0%) missing values Missing
materialEntityID has 584201 (100.0%) missing values Missing
materialEntityRemarks has 584201 (100.0%) missing values Missing
verbatimLabel has 584201 (100.0%) missing values Missing
materialSampleID has 584201 (100.0%) missing values Missing
eventID has 584201 (100.0%) missing values Missing
parentEventID has 584201 (100.0%) missing values Missing
eventType has 584201 (100.0%) missing values Missing
fieldNumber has 584193 (> 99.9%) missing values Missing
eventDate has 39140 (6.7%) missing values Missing
eventTime has 584201 (100.0%) missing values Missing
startDayOfYear has 86170 (14.8%) missing values Missing
endDayOfYear has 86170 (14.8%) missing values Missing
year has 39600 (6.8%) missing values Missing
month has 59025 (10.1%) missing values Missing
day has 100844 (17.3%) missing values Missing
habitat has 584201 (100.0%) missing values Missing
samplingProtocol has 584201 (100.0%) missing values Missing
sampleSizeValue has 584201 (100.0%) missing values Missing
sampleSizeUnit has 584201 (100.0%) missing values Missing
samplingEffort has 584201 (100.0%) missing values Missing
fieldNotes has 584201 (100.0%) missing values Missing
eventRemarks has 584201 (100.0%) missing values Missing
locationID has 584201 (100.0%) missing values Missing
higherGeographyID has 584201 (100.0%) missing values Missing
continent has 10069 (1.7%) missing values Missing
waterBody has 555994 (95.2%) missing values Missing
islandGroup has 564324 (96.6%) missing values Missing
island has 576136 (98.6%) missing values Missing
countryCode has 10837 (1.9%) missing values Missing
stateProvince has 17001 (2.9%) missing values Missing
county has 191557 (32.8%) missing values Missing
municipality has 584201 (100.0%) missing values Missing
verbatimLocality has 584201 (100.0%) missing values Missing
verbatimElevation has 331608 (56.8%) missing values Missing
verticalDatum has 584201 (100.0%) missing values Missing
verbatimDepth has 584201 (100.0%) missing values Missing
minimumDistanceAboveSurfaceInMeters has 584201 (100.0%) missing values Missing
maximumDistanceAboveSurfaceInMeters has 584201 (100.0%) missing values Missing
locationAccordingTo has 584201 (100.0%) missing values Missing
locationRemarks has 584201 (100.0%) missing values Missing
decimalLatitude has 162667 (27.8%) missing values Missing
decimalLongitude has 162667 (27.8%) missing values Missing
coordinateUncertaintyInMeters has 439218 (75.2%) missing values Missing
coordinatePrecision has 584201 (100.0%) missing values Missing
pointRadiusSpatialFit has 584201 (100.0%) missing values Missing
verbatimCoordinateSystem has 584201 (100.0%) missing values Missing
verbatimSRS has 584201 (100.0%) missing values Missing
footprintWKT has 584201 (100.0%) missing values Missing
footprintSRS has 584201 (100.0%) missing values Missing
footprintSpatialFit has 584201 (100.0%) missing values Missing
georeferencedBy has 584201 (100.0%) missing values Missing
georeferencedDate has 584201 (100.0%) missing values Missing
georeferenceProtocol has 439136 (75.2%) missing values Missing
georeferenceSources has 584201 (100.0%) missing values Missing
georeferenceRemarks has 443625 (75.9%) missing values Missing
geologicalContextID has 584201 (100.0%) missing values Missing
earliestEonOrLowestEonothem has 584201 (100.0%) missing values Missing
latestEonOrHighestEonothem has 584201 (100.0%) missing values Missing
earliestEraOrLowestErathem has 584201 (100.0%) missing values Missing
latestEraOrHighestErathem has 584201 (100.0%) missing values Missing
earliestPeriodOrLowestSystem has 584201 (100.0%) missing values Missing
latestPeriodOrHighestSystem has 584201 (100.0%) missing values Missing
earliestEpochOrLowestSeries has 584201 (100.0%) missing values Missing
latestEpochOrHighestSeries has 584201 (100.0%) missing values Missing
earliestAgeOrLowestStage has 584201 (100.0%) missing values Missing
latestAgeOrHighestStage has 584201 (100.0%) missing values Missing
lowestBiostratigraphicZone has 584201 (100.0%) missing values Missing
highestBiostratigraphicZone has 584201 (100.0%) missing values Missing
lithostratigraphicTerms has 584201 (100.0%) missing values Missing
group has 584201 (100.0%) missing values Missing
formation has 584201 (100.0%) missing values Missing
member has 584201 (100.0%) missing values Missing
bed has 584201 (100.0%) missing values Missing
identificationID has 584201 (100.0%) missing values Missing
verbatimIdentification has 584201 (100.0%) missing values Missing
identificationQualifier has 583784 (99.9%) missing values Missing
typeStatus has 571070 (97.8%) missing values Missing
identifiedBy has 584125 (> 99.9%) missing values Missing
identifiedByID has 584201 (100.0%) missing values Missing
dateIdentified has 584201 (100.0%) missing values Missing
identificationReferences has 584201 (100.0%) missing values Missing
identificationVerificationStatus has 584201 (100.0%) missing values Missing
identificationRemarks has 584201 (100.0%) missing values Missing
taxonID has 584201 (100.0%) missing values Missing
scientificNameID has 584201 (100.0%) missing values Missing
parentNameUsageID has 584201 (100.0%) missing values Missing
originalNameUsageID has 584201 (100.0%) missing values Missing
nameAccordingToID has 584201 (100.0%) missing values Missing
namePublishedInID has 584201 (100.0%) missing values Missing
taxonConceptID has 584201 (100.0%) missing values Missing
acceptedNameUsage has 584201 (100.0%) missing values Missing
parentNameUsage has 584201 (100.0%) missing values Missing
originalNameUsage has 584201 (100.0%) missing values Missing
nameAccordingTo has 584201 (100.0%) missing values Missing
namePublishedIn has 584201 (100.0%) missing values Missing
namePublishedInYear has 584201 (100.0%) missing values Missing
order has 189040 (32.4%) missing values Missing
superfamily has 584201 (100.0%) missing values Missing
subfamily has 584201 (100.0%) missing values Missing
tribe has 584201 (100.0%) missing values Missing
subtribe has 584201 (100.0%) missing values Missing
subgenus has 584201 (100.0%) missing values Missing
infragenericEpithet has 584201 (100.0%) missing values Missing
specificEpithet has 15011 (2.6%) missing values Missing
infraspecificEpithet has 559230 (95.7%) missing values Missing
cultivarEpithet has 584201 (100.0%) missing values Missing
verbatimTaxonRank has 584201 (100.0%) missing values Missing
vernacularName has 584201 (100.0%) missing values Missing
nomenclaturalCode has 584201 (100.0%) missing values Missing
nomenclaturalStatus has 584201 (100.0%) missing values Missing
taxonRemarks has 584201 (100.0%) missing values Missing
elevation has 332110 (56.8%) missing values Missing
elevationAccuracy has 333288 (57.1%) missing values Missing
depth has 584201 (100.0%) missing values Missing
depthAccuracy has 584201 (100.0%) missing values Missing
distanceFromCentroidInMeters has 581727 (99.6%) missing values Missing
mediaType has 579082 (99.1%) missing values Missing
orderKey has 189040 (32.4%) missing values Missing
subgenusKey has 584201 (100.0%) missing values Missing
speciesKey has 15011 (2.6%) missing values Missing
species has 15011 (2.6%) missing values Missing
typifiedName has 584201 (100.0%) missing values Missing
repatriated has 10596 (1.8%) missing values Missing
relativeOrganismQuantity has 584201 (100.0%) missing values Missing
projectId has 584201 (100.0%) missing values Missing
gbifRegion has 11409 (2.0%) missing values Missing
level0Gid has 173676 (29.7%) missing values Missing
level0Name has 173676 (29.7%) missing values Missing
level1Gid has 174349 (29.8%) missing values Missing
level1Name has 174349 (29.8%) missing values Missing
level2Gid has 186113 (31.9%) missing values Missing
level2Name has 186171 (31.9%) missing values Missing
level3Gid has 532468 (91.1%) missing values Missing
level3Name has 532843 (91.2%) missing values Missing
iucnRedListCategory has 23468 (4.0%) missing values Missing
individualCount is highly skewed (γ1 = 94.46551091) Skewed
coordinateUncertaintyInMeters is highly skewed (γ1 = 27.97550952) Skewed
elevationAccuracy is highly skewed (γ1 = 20.71091822) Skewed
orderKey is highly skewed (γ1 = -27.24937495) Skewed
gbifID has unique values Unique
occurrenceID has unique values Unique
catalogNumber has unique values Unique
accessRights is an unsupported type, check if it needs cleaning or further analysis Unsupported
bibliographicCitation is an unsupported type, check if it needs cleaning or further analysis Unsupported
language is an unsupported type, check if it needs cleaning or further analysis Unsupported
references is an unsupported type, check if it needs cleaning or further analysis Unsupported
rightsHolder is an unsupported type, check if it needs cleaning or further analysis Unsupported
type is an unsupported type, check if it needs cleaning or further analysis Unsupported
datasetID is an unsupported type, check if it needs cleaning or further analysis Unsupported
ownerInstitutionCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
informationWithheld is an unsupported type, check if it needs cleaning or further analysis Unsupported
dataGeneralizations is an unsupported type, check if it needs cleaning or further analysis Unsupported
dynamicProperties is an unsupported type, check if it needs cleaning or further analysis Unsupported
recordedBy is an unsupported type, check if it needs cleaning or further analysis Unsupported
recordedByID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantityType is an unsupported type, check if it needs cleaning or further analysis Unsupported
reproductiveCondition is an unsupported type, check if it needs cleaning or further analysis Unsupported
caste is an unsupported type, check if it needs cleaning or further analysis Unsupported
behavior is an unsupported type, check if it needs cleaning or further analysis Unsupported
vitality is an unsupported type, check if it needs cleaning or further analysis Unsupported
establishmentMeans is an unsupported type, check if it needs cleaning or further analysis Unsupported
degreeOfEstablishment is an unsupported type, check if it needs cleaning or further analysis Unsupported
pathway is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceVerificationStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
disposition is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOccurrences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedReferences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedTaxa is an unsupported type, check if it needs cleaning or further analysis Unsupported
otherCatalogNumbers is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismName is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismScope is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOrganisms is an unsupported type, check if it needs cleaning or further analysis Unsupported
previousIdentifications is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityID is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLabel is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialSampleID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentEventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventType is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventTime is an unsupported type, check if it needs cleaning or further analysis Unsupported
habitat is an unsupported type, check if it needs cleaning or further analysis Unsupported
samplingProtocol is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeValue is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeUnit is an unsupported type, check if it needs cleaning or further analysis Unsupported
samplingEffort is an unsupported type, check if it needs cleaning or further analysis Unsupported
fieldNotes is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationID is an unsupported type, check if it needs cleaning or further analysis Unsupported
higherGeographyID is an unsupported type, check if it needs cleaning or further analysis Unsupported
municipality is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLocality is an unsupported type, check if it needs cleaning or further analysis Unsupported
verticalDatum is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimDepth is an unsupported type, check if it needs cleaning or further analysis Unsupported
minimumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
maximumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationAccordingTo is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
coordinatePrecision is an unsupported type, check if it needs cleaning or further analysis Unsupported
pointRadiusSpatialFit is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimCoordinateSystem is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintWKT is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSpatialFit is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferencedBy is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferencedDate is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceSources is an unsupported type, check if it needs cleaning or further analysis Unsupported
geologicalContextID is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEonOrLowestEonothem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEonOrHighestEonothem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEraOrLowestErathem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEraOrHighestErathem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestPeriodOrLowestSystem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestPeriodOrHighestSystem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEpochOrLowestSeries is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEpochOrHighestSeries is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestAgeOrLowestStage is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestAgeOrHighestStage is an unsupported type, check if it needs cleaning or further analysis Unsupported
lowestBiostratigraphicZone is an unsupported type, check if it needs cleaning or further analysis Unsupported
highestBiostratigraphicZone is an unsupported type, check if it needs cleaning or further analysis Unsupported
lithostratigraphicTerms is an unsupported type, check if it needs cleaning or further analysis Unsupported
group is an unsupported type, check if it needs cleaning or further analysis Unsupported
formation is an unsupported type, check if it needs cleaning or further analysis Unsupported
member is an unsupported type, check if it needs cleaning or further analysis Unsupported
bed is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationID is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimIdentification is an unsupported type, check if it needs cleaning or further analysis Unsupported
identifiedByID is an unsupported type, check if it needs cleaning or further analysis Unsupported
dateIdentified is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationReferences is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationVerificationStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonID is an unsupported type, check if it needs cleaning or further analysis Unsupported
scientificNameID is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentNameUsageID is an unsupported type, check if it needs cleaning or further analysis Unsupported
originalNameUsageID is an unsupported type, check if it needs cleaning or further analysis Unsupported
nameAccordingToID is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedInID is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonConceptID is an unsupported type, check if it needs cleaning or further analysis Unsupported
acceptedNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
originalNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
nameAccordingTo is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedIn is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedInYear is an unsupported type, check if it needs cleaning or further analysis Unsupported
superfamily is an unsupported type, check if it needs cleaning or further analysis Unsupported
subfamily is an unsupported type, check if it needs cleaning or further analysis Unsupported
tribe is an unsupported type, check if it needs cleaning or further analysis Unsupported
subtribe is an unsupported type, check if it needs cleaning or further analysis Unsupported
subgenus is an unsupported type, check if it needs cleaning or further analysis Unsupported
infragenericEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
cultivarEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimTaxonRank is an unsupported type, check if it needs cleaning or further analysis Unsupported
vernacularName is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
depth is an unsupported type, check if it needs cleaning or further analysis Unsupported
depthAccuracy is an unsupported type, check if it needs cleaning or further analysis Unsupported
subgenusKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
typifiedName is an unsupported type, check if it needs cleaning or further analysis Unsupported
relativeOrganismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
projectId is an unsupported type, check if it needs cleaning or further analysis Unsupported
elevationAccuracy has 220652 (37.8%) zeros Zeros

Reproduction

Analysis started2025-01-07 15:48:36.697061
Analysis finished2025-01-07 15:48:54.819704
Duration18.12 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Real number (ℝ)

Unique 

Distinct584201
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1380400383
Minimum1317202457
Maximum4976690427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:54.851626image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1317202457
5-th percentile1317498697
Q11318681478
median1320157420
Q31321643363
95-th percentile1322833209
Maximum4976690427
Range3659487970
Interquartile range (IQR)2961885

Descriptive statistics

Standard deviation443319072.9
Coefficient of variation (CV)0.3211525282
Kurtosis57.93825165
Mean1380400383
Median Absolute Deviation (MAD)1480952
Skewness7.668417357
Sum8.064312841 × 1014
Variance1.965318004 × 1017
MonotonicityNot monotonic
2025-01-07T10:48:54.913950image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1321417984 1
 
< 0.1%
1317203362 1
 
< 0.1%
1317203927 1
 
< 0.1%
1317204107 1
 
< 0.1%
1322537851 1
 
< 0.1%
1322539748 1
 
< 0.1%
1317211425 1
 
< 0.1%
1322545681 1
 
< 0.1%
1317214456 1
 
< 0.1%
1321375863 1
 
< 0.1%
Other values (584191) 584191
> 99.9%
ValueCountFrequency (%)
1317202457 1
< 0.1%
1317202479 1
< 0.1%
1317202491 1
< 0.1%
1317202510 1
< 0.1%
1317202528 1
< 0.1%
ValueCountFrequency (%)
4976690427 1
< 0.1%
4976689754 1
< 0.1%
4976689697 1
< 0.1%
4976689262 1
< 0.1%
4976685425 1
< 0.1%

accessRights
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

bibliographicCitation
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

language
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:54.954463image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4089407
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCC0_1_0
2nd rowCC0_1_0
3rd rowCC0_1_0
4th rowCC0_1_0
5th rowCC0_1_0
ValueCountFrequency (%)
cc0_1_0 584201
100.0%
2025-01-07T10:48:55.044408image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1168402
28.6%
0 1168402
28.6%
_ 1168402
28.6%
1 584201
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4089407
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1168402
28.6%
0 1168402
28.6%
_ 1168402
28.6%
1 584201
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4089407
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1168402
28.6%
0 1168402
28.6%
_ 1168402
28.6%
1 584201
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4089407
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1168402
28.6%
0 1168402
28.6%
_ 1168402
28.6%
1 584201
14.3%
Distinct11116
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:55.164236image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters11684020
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6239 ?
Unique (%)1.1%

Sample

1st row2022-03-25T16:29:00Z
2nd row2022-12-14T12:20:00Z
3rd row2022-07-25T13:54:00Z
4th row2022-03-25T16:12:00Z
5th row2022-03-25T16:41:00Z
ValueCountFrequency (%)
2022-08-17t10:53:00z 3308
 
0.6%
2022-08-17t10:58:00z 3292
 
0.6%
2022-08-17t10:59:00z 3292
 
0.6%
2022-08-17t10:54:00z 3283
 
0.6%
2022-08-17t10:57:00z 3269
 
0.6%
2022-08-17t10:56:00z 3263
 
0.6%
2022-08-17t11:00:00z 3247
 
0.6%
2022-08-17t11:01:00z 3245
 
0.6%
2022-08-17t11:03:00z 3243
 
0.6%
2022-08-17t11:15:00z 3237
 
0.6%
Other values (11106) 551522
94.4%
2025-01-07T10:48:55.341980image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2825947
24.2%
2 1945269
16.6%
1 1362306
11.7%
- 1168402
10.0%
: 1168402
10.0%
T 584201
 
5.0%
Z 584201
 
5.0%
8 454189
 
3.9%
5 397958
 
3.4%
3 369937
 
3.2%
Other values (4) 823208
 
7.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11684020
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 2825947
24.2%
2 1945269
16.6%
1 1362306
11.7%
- 1168402
10.0%
: 1168402
10.0%
T 584201
 
5.0%
Z 584201
 
5.0%
8 454189
 
3.9%
5 397958
 
3.4%
3 369937
 
3.2%
Other values (4) 823208
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11684020
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 2825947
24.2%
2 1945269
16.6%
1 1362306
11.7%
- 1168402
10.0%
: 1168402
10.0%
T 584201
 
5.0%
Z 584201
 
5.0%
8 454189
 
3.9%
5 397958
 
3.4%
3 369937
 
3.2%
Other values (4) 823208
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11684020
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 2825947
24.2%
2 1945269
16.6%
1 1362306
11.7%
- 1168402
10.0%
: 1168402
10.0%
T 584201
 
5.0%
Z 584201
 
5.0%
8 454189
 
3.9%
5 397958
 
3.4%
3 369937
 
3.2%
Other values (4) 823208
 
7.0%

publisher
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:55.412191image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length59
Mean length59
Min length59

Characters and Unicode

Total characters34467859
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNational Museum of Natural History, Smithsonian Institution
2nd rowNational Museum of Natural History, Smithsonian Institution
3rd rowNational Museum of Natural History, Smithsonian Institution
4th rowNational Museum of Natural History, Smithsonian Institution
5th rowNational Museum of Natural History, Smithsonian Institution
ValueCountFrequency (%)
national 584201
14.3%
museum 584201
14.3%
of 584201
14.3%
natural 584201
14.3%
history 584201
14.3%
smithsonian 584201
14.3%
institution 584201
14.3%
2025-01-07T10:48:55.520393image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 4089407
11.9%
i 3505206
10.2%
3505206
10.2%
o 2921005
 
8.5%
a 2921005
 
8.5%
n 2921005
 
8.5%
s 2336804
 
6.8%
u 2336804
 
6.8%
N 1168402
 
3.4%
m 1168402
 
3.4%
Other values (11) 7594613
22.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 34467859
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 4089407
11.9%
i 3505206
10.2%
3505206
10.2%
o 2921005
 
8.5%
a 2921005
 
8.5%
n 2921005
 
8.5%
s 2336804
 
6.8%
u 2336804
 
6.8%
N 1168402
 
3.4%
m 1168402
 
3.4%
Other values (11) 7594613
22.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 34467859
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 4089407
11.9%
i 3505206
10.2%
3505206
10.2%
o 2921005
 
8.5%
a 2921005
 
8.5%
n 2921005
 
8.5%
s 2336804
 
6.8%
u 2336804
 
6.8%
N 1168402
 
3.4%
m 1168402
 
3.4%
Other values (11) 7594613
22.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 34467859
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 4089407
11.9%
i 3505206
10.2%
3505206
10.2%
o 2921005
 
8.5%
a 2921005
 
8.5%
n 2921005
 
8.5%
s 2336804
 
6.8%
u 2336804
 
6.8%
N 1168402
 
3.4%
m 1168402
 
3.4%
Other values (11) 7594613
22.0%

references
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

rightsHolder
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

type
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:55.573499image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters16941829
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:lsid:biocol.org:col:34871
2nd rowurn:lsid:biocol.org:col:34871
3rd rowurn:lsid:biocol.org:col:34871
4th rowurn:lsid:biocol.org:col:34871
5th rowurn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
urn:lsid:biocol.org:col:34871 584201
100.0%
2025-01-07T10:48:55.680783image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2336804
13.8%
: 2336804
13.8%
l 1752603
 
10.3%
r 1168402
 
6.9%
c 1168402
 
6.9%
i 1168402
 
6.9%
u 584201
 
3.4%
s 584201
 
3.4%
d 584201
 
3.4%
n 584201
 
3.4%
Other values (8) 4673608
27.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16941829
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2336804
13.8%
: 2336804
13.8%
l 1752603
 
10.3%
r 1168402
 
6.9%
c 1168402
 
6.9%
i 1168402
 
6.9%
u 584201
 
3.4%
s 584201
 
3.4%
d 584201
 
3.4%
n 584201
 
3.4%
Other values (8) 4673608
27.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16941829
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2336804
13.8%
: 2336804
13.8%
l 1752603
 
10.3%
r 1168402
 
6.9%
c 1168402
 
6.9%
i 1168402
 
6.9%
u 584201
 
3.4%
s 584201
 
3.4%
d 584201
 
3.4%
n 584201
 
3.4%
Other values (8) 4673608
27.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16941829
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2336804
13.8%
: 2336804
13.8%
l 1752603
 
10.3%
r 1168402
 
6.9%
c 1168402
 
6.9%
i 1168402
 
6.9%
u 584201
 
3.4%
s 584201
 
3.4%
d 584201
 
3.4%
n 584201
 
3.4%
Other values (8) 4673608
27.6%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:55.737383image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters26289045
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0
2nd rowurn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0
3rd rowurn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0
4th rowurn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0
5th rowurn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0
ValueCountFrequency (%)
urn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0 584201
100.0%
2025-01-07T10:48:55.842324image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2921005
 
11.1%
- 2336804
 
8.9%
u 1752603
 
6.7%
c 1752603
 
6.7%
b 1752603
 
6.7%
0 1752603
 
6.7%
7 1752603
 
6.7%
d 1752603
 
6.7%
a 1168402
 
4.4%
f 1168402
 
4.4%
Other values (10) 8178814
31.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26289045
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 2921005
 
11.1%
- 2336804
 
8.9%
u 1752603
 
6.7%
c 1752603
 
6.7%
b 1752603
 
6.7%
0 1752603
 
6.7%
7 1752603
 
6.7%
d 1752603
 
6.7%
a 1168402
 
4.4%
f 1168402
 
4.4%
Other values (10) 8178814
31.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26289045
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 2921005
 
11.1%
- 2336804
 
8.9%
u 1752603
 
6.7%
c 1752603
 
6.7%
b 1752603
 
6.7%
0 1752603
 
6.7%
7 1752603
 
6.7%
d 1752603
 
6.7%
a 1168402
 
4.4%
f 1168402
 
4.4%
Other values (10) 8178814
31.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26289045
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 2921005
 
11.1%
- 2336804
 
8.9%
u 1752603
 
6.7%
c 1752603
 
6.7%
b 1752603
 
6.7%
0 1752603
 
6.7%
7 1752603
 
6.7%
d 1752603
 
6.7%
a 1168402
 
4.4%
f 1168402
 
4.4%
Other values (10) 8178814
31.1%

datasetID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:55.882323image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2336804
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 584201
100.0%
2025-01-07T10:48:55.972926image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 584201
25.0%
S 584201
25.0%
N 584201
25.0%
M 584201
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2336804
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 584201
25.0%
S 584201
25.0%
N 584201
25.0%
M 584201
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2336804
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 584201
25.0%
S 584201
25.0%
N 584201
25.0%
M 584201
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2336804
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 584201
25.0%
S 584201
25.0%
N 584201
25.0%
M 584201
25.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:56.012178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2336804
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHERP
2nd rowHERP
3rd rowHERP
4th rowHERP
5th rowHERP
ValueCountFrequency (%)
herp 584201
100.0%
2025-01-07T10:48:56.099738image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
H 584201
25.0%
E 584201
25.0%
R 584201
25.0%
P 584201
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2336804
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
H 584201
25.0%
E 584201
25.0%
R 584201
25.0%
P 584201
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2336804
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
H 584201
25.0%
E 584201
25.0%
R 584201
25.0%
P 584201
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2336804
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
H 584201
25.0%
E 584201
25.0%
R 584201
25.0%
P 584201
25.0%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:56.144245image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11099819
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 584201
33.3%
extant 584201
33.3%
biology 584201
33.3%
2025-01-07T10:48:56.238889image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1168402
 
10.5%
t 1168402
 
10.5%
1168402
 
10.5%
o 1168402
 
10.5%
H 584201
 
5.3%
E 584201
 
5.3%
M 584201
 
5.3%
x 584201
 
5.3%
a 584201
 
5.3%
B 584201
 
5.3%
Other values (5) 2921005
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11099819
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1168402
 
10.5%
t 1168402
 
10.5%
1168402
 
10.5%
o 1168402
 
10.5%
H 584201
 
5.3%
E 584201
 
5.3%
M 584201
 
5.3%
x 584201
 
5.3%
a 584201
 
5.3%
B 584201
 
5.3%
Other values (5) 2921005
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11099819
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1168402
 
10.5%
t 1168402
 
10.5%
1168402
 
10.5%
o 1168402
 
10.5%
H 584201
 
5.3%
E 584201
 
5.3%
M 584201
 
5.3%
x 584201
 
5.3%
a 584201
 
5.3%
B 584201
 
5.3%
Other values (5) 2921005
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11099819
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1168402
 
10.5%
t 1168402
 
10.5%
1168402
 
10.5%
o 1168402
 
10.5%
H 584201
 
5.3%
E 584201
 
5.3%
M 584201
 
5.3%
x 584201
 
5.3%
a 584201
 
5.3%
B 584201
 
5.3%
Other values (5) 2921005
26.3%

ownerInstitutionCode
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:56.357645image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length18
Mean length18.00021739
Min length18

Characters and Unicode

Total characters10515745
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESERVED_SPECIMEN
2nd rowPRESERVED_SPECIMEN
3rd rowPRESERVED_SPECIMEN
4th rowPRESERVED_SPECIMEN
5th rowPRESERVED_SPECIMEN
ValueCountFrequency (%)
preserved_specimen 584074
> 99.9%
machine_observation 127
 
< 0.1%
2025-01-07T10:48:56.460762image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 2920624
27.8%
R 1168275
11.1%
S 1168275
11.1%
P 1168148
 
11.1%
N 584328
 
5.6%
I 584328
 
5.6%
V 584201
 
5.6%
_ 584201
 
5.6%
M 584201
 
5.6%
C 584201
 
5.6%
Other values (6) 584963
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10515745
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 2920624
27.8%
R 1168275
11.1%
S 1168275
11.1%
P 1168148
 
11.1%
N 584328
 
5.6%
I 584328
 
5.6%
V 584201
 
5.6%
_ 584201
 
5.6%
M 584201
 
5.6%
C 584201
 
5.6%
Other values (6) 584963
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10515745
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 2920624
27.8%
R 1168275
11.1%
S 1168275
11.1%
P 1168148
 
11.1%
N 584328
 
5.6%
I 584328
 
5.6%
V 584201
 
5.6%
_ 584201
 
5.6%
M 584201
 
5.6%
C 584201
 
5.6%
Other values (6) 584963
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10515745
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 2920624
27.8%
R 1168275
11.1%
S 1168275
11.1%
P 1168148
 
11.1%
N 584328
 
5.6%
I 584328
 
5.6%
V 584201
 
5.6%
_ 584201
 
5.6%
M 584201
 
5.6%
C 584201
 
5.6%
Other values (6) 584963
 
5.6%

informationWithheld
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

dataGeneralizations
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

dynamicProperties
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

occurrenceID
Text

Unique 

Distinct584201
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:56.751764image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters36804663
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique584201 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/3000ac9b1-ec0b-4be2-939f-464ad355cc84
2nd rowhttp://n2t.net/ark:/65665/30010adfb-58e1-4e98-8d39-ee055b3463fa
3rd rowhttp://n2t.net/ark:/65665/30012ab17-d2a1-470c-a774-540bc6cffb00
4th rowhttp://n2t.net/ark:/65665/3ec02d332-deb7-4b55-ba3d-5a5d6ca577c9
5th rowhttp://n2t.net/ark:/65665/3ec19a125-2484-4fa3-b6b7-7d87199a6994
ValueCountFrequency (%)
http://n2t.net/ark:/65665/300b050bd-5eb9-4ac1-8001-a36bcdda9025 1
 
< 0.1%
http://n2t.net/ark:/65665/3ba6decff-71e8-46e4-a858-b7c2c8756031 1
 
< 0.1%
http://n2t.net/ark:/65665/3000ac9b1-ec0b-4be2-939f-464ad355cc84 1
 
< 0.1%
http://n2t.net/ark:/65665/30010adfb-58e1-4e98-8d39-ee055b3463fa 1
 
< 0.1%
http://n2t.net/ark:/65665/30012ab17-d2a1-470c-a774-540bc6cffb00 1
 
< 0.1%
http://n2t.net/ark:/65665/3ec02d332-deb7-4b55-ba3d-5a5d6ca577c9 1
 
< 0.1%
http://n2t.net/ark:/65665/3ec19a125-2484-4fa3-b6b7-7d87199a6994 1
 
< 0.1%
http://n2t.net/ark:/65665/3006575b6-ca0a-42bd-b75d-3241cc3e332d 1
 
< 0.1%
http://n2t.net/ark:/65665/3ec5d93fc-e189-4a2f-b46a-9c0e7204ab35 1
 
< 0.1%
http://n2t.net/ark:/65665/3b8ab56c5-4513-4fa8-a5eb-22f04f926442 1
 
< 0.1%
Other values (584191) 584191
> 99.9%
2025-01-07T10:48:57.115252image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 2921005
 
7.9%
6 2847614
 
7.7%
- 2336804
 
6.3%
t 2336804
 
6.3%
5 2265995
 
6.2%
a 1826256
 
5.0%
e 1681096
 
4.6%
2 1680524
 
4.6%
3 1680017
 
4.6%
4 1678083
 
4.6%
Other values (16) 15550465
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36804663
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 2921005
 
7.9%
6 2847614
 
7.7%
- 2336804
 
6.3%
t 2336804
 
6.3%
5 2265995
 
6.2%
a 1826256
 
5.0%
e 1681096
 
4.6%
2 1680524
 
4.6%
3 1680017
 
4.6%
4 1678083
 
4.6%
Other values (16) 15550465
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36804663
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 2921005
 
7.9%
6 2847614
 
7.7%
- 2336804
 
6.3%
t 2336804
 
6.3%
5 2265995
 
6.2%
a 1826256
 
5.0%
e 1681096
 
4.6%
2 1680524
 
4.6%
3 1680017
 
4.6%
4 1678083
 
4.6%
Other values (16) 15550465
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36804663
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 2921005
 
7.9%
6 2847614
 
7.7%
- 2336804
 
6.3%
t 2336804
 
6.3%
5 2265995
 
6.2%
a 1826256
 
5.0%
e 1681096
 
4.6%
2 1680524
 
4.6%
3 1680017
 
4.6%
4 1678083
 
4.6%
Other values (16) 15550465
42.3%

catalogNumber
Text

Unique 

Distinct584201
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:57.485353image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length11
Mean length10.93256944
Min length6

Characters and Unicode

Total characters6386818
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique584201 ?
Unique (%)100.0%

Sample

1st rowUSNM 231889
2nd rowUSNM 487703
3rd rowUSNM 297347
4th rowUSNM 322261
5th rowUSNM 319170
ValueCountFrequency (%)
usnm 584201
49.5%
herp 5833
 
0.5%
tissue 5706
 
0.5%
image 127
 
< 0.1%
2731 3
 
< 0.1%
2822 3
 
< 0.1%
2817 3
 
< 0.1%
2846 3
 
< 0.1%
2715 3
 
< 0.1%
2744 3
 
< 0.1%
Other values (581072) 584183
49.5%
2025-01-07T10:48:57.912152image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
595867
 
9.3%
S 584201
 
9.1%
U 584201
 
9.1%
N 584201
 
9.1%
M 584201
 
9.1%
4 393545
 
6.2%
2 393142
 
6.2%
3 392798
 
6.2%
1 391284
 
6.1%
5 383581
 
6.0%
Other values (17) 1499797
23.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6386818
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
595867
 
9.3%
S 584201
 
9.1%
U 584201
 
9.1%
N 584201
 
9.1%
M 584201
 
9.1%
4 393545
 
6.2%
2 393142
 
6.2%
3 392798
 
6.2%
1 391284
 
6.1%
5 383581
 
6.0%
Other values (17) 1499797
23.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6386818
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
595867
 
9.3%
S 584201
 
9.1%
U 584201
 
9.1%
N 584201
 
9.1%
M 584201
 
9.1%
4 393545
 
6.2%
2 393142
 
6.2%
3 392798
 
6.2%
1 391284
 
6.1%
5 383581
 
6.0%
Other values (17) 1499797
23.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6386818
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
595867
 
9.3%
S 584201
 
9.1%
U 584201
 
9.1%
N 584201
 
9.1%
M 584201
 
9.1%
4 393545
 
6.2%
2 393142
 
6.2%
3 392798
 
6.2%
1 391284
 
6.1%
5 383581
 
6.0%
Other values (17) 1499797
23.5%

recordNumber
Text

Missing 

Distinct273
Distinct (%)98.9%
Missing583925
Missing (%)> 99.9%
Memory size4.5 MiB
2025-01-07T10:48:58.105317image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.460144928
Min length1

Characters and Unicode

Total characters2335
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique271 ?
Unique (%)98.2%

Sample

1st rowRWM 20004
2nd rowRWM 19953
3rd rowRWM 19978
4th rowRWM 19932
5th rowRWM 19955
ValueCountFrequency (%)
rwm 182
33.2%
gmu 74
 
13.5%
lc 15
 
2.7%
8 3
 
0.5%
19897 2
 
0.4%
19987 1
 
0.2%
19953 1
 
0.2%
3030 1
 
0.2%
19921 1
 
0.2%
19900 1
 
0.2%
Other values (267) 267
48.7%
2025-01-07T10:48:58.364720image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
272
11.6%
9 260
11.1%
M 257
11.0%
0 245
10.5%
1 190
8.1%
R 182
7.8%
W 182
7.8%
2 165
7.1%
3 95
 
4.1%
G 75
 
3.2%
Other values (9) 412
17.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2335
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
272
11.6%
9 260
11.1%
M 257
11.0%
0 245
10.5%
1 190
8.1%
R 182
7.8%
W 182
7.8%
2 165
7.1%
3 95
 
4.1%
G 75
 
3.2%
Other values (9) 412
17.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2335
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
272
11.6%
9 260
11.1%
M 257
11.0%
0 245
10.5%
1 190
8.1%
R 182
7.8%
W 182
7.8%
2 165
7.1%
3 95
 
4.1%
G 75
 
3.2%
Other values (9) 412
17.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2335
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
272
11.6%
9 260
11.1%
M 257
11.0%
0 245
10.5%
1 190
8.1%
R 182
7.8%
W 182
7.8%
2 165
7.1%
3 95
 
4.1%
G 75
 
3.2%
Other values (9) 412
17.6%

recordedBy
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

recordedByID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

individualCount
Real number (ℝ)

Skewed 

Distinct158
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.178484313
Minimum0
Maximum952
Zeros1007
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:58.440140image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum952
Range952
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.291942708
Coefficient of variation (CV)3.641917556
Kurtosis15525.57897
Mean1.178484313
Median Absolute Deviation (MAD)0
Skewness94.46551091
Sum688467
Variance18.42077221
MonotonicityNot monotonic
2025-01-07T10:48:58.500948image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 576101
98.6%
2 1312
 
0.2%
0 1007
 
0.2%
3 830
 
0.1%
5 523
 
0.1%
4 522
 
0.1%
6 386
 
0.1%
7 339
 
0.1%
8 271
 
< 0.1%
10 257
 
< 0.1%
Other values (148) 2649
 
0.5%
ValueCountFrequency (%)
0 1007
 
0.2%
1 576101
98.6%
2 1312
 
0.2%
3 830
 
0.1%
4 522
 
0.1%
ValueCountFrequency (%)
952 2
< 0.1%
950 1
 
< 0.1%
600 1
 
< 0.1%
500 4
< 0.1%
402 1
 
< 0.1%

organismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

organismQuantityType
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

sex
Text

Missing 

Distinct3
Distinct (%)< 0.1%
Missing531942
Missing (%)91.1%
Memory size4.5 MiB
2025-01-07T10:48:58.538109image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length4
Mean length4.859507453
Min length4

Characters and Unicode

Total characters253953
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowMALE
2nd rowMALE
3rd rowFEMALE
4th rowMALE
5th rowFEMALE
ValueCountFrequency (%)
male 29804
57.0%
female 22454
43.0%
hermaphrodite 1
 
< 0.1%
2025-01-07T10:48:58.628506image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 74714
29.4%
M 52259
20.6%
A 52259
20.6%
L 52258
20.6%
F 22454
 
8.8%
H 2
 
< 0.1%
R 2
 
< 0.1%
P 1
 
< 0.1%
O 1
 
< 0.1%
D 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 253953
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 74714
29.4%
M 52259
20.6%
A 52259
20.6%
L 52258
20.6%
F 22454
 
8.8%
H 2
 
< 0.1%
R 2
 
< 0.1%
P 1
 
< 0.1%
O 1
 
< 0.1%
D 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 253953
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 74714
29.4%
M 52259
20.6%
A 52259
20.6%
L 52258
20.6%
F 22454
 
8.8%
H 2
 
< 0.1%
R 2
 
< 0.1%
P 1
 
< 0.1%
O 1
 
< 0.1%
D 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 253953
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 74714
29.4%
M 52259
20.6%
A 52259
20.6%
L 52258
20.6%
F 22454
 
8.8%
H 2
 
< 0.1%
R 2
 
< 0.1%
P 1
 
< 0.1%
O 1
 
< 0.1%
D 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

lifeStage
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing542754
Missing (%)92.9%
Memory size4.5 MiB
2025-01-07T10:48:58.679759image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.744082805
Min length3

Characters and Unicode

Total characters279522
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLarva
2nd rowEgg
3rd rowLarva
4th rowJuvenile
5th rowJuvenile
ValueCountFrequency (%)
juvenile 20321
49.0%
larva 11464
27.7%
adult 3710
 
9.0%
hatchling 2380
 
5.7%
embryo 1048
 
2.5%
egg 838
 
2.0%
neonate 656
 
1.6%
subadult 528
 
1.3%
eft 387
 
0.9%
immature 88
 
0.2%
Other values (2) 27
 
0.1%
2025-01-07T10:48:58.785490image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 42069
15.1%
v 31785
11.4%
l 26962
9.6%
a 26603
9.5%
u 25179
9.0%
n 23357
8.4%
i 22701
8.1%
J 20321
7.3%
r 12600
 
4.5%
L 11464
 
4.1%
Other values (20) 36481
13.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 279522
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 42069
15.1%
v 31785
11.4%
l 26962
9.6%
a 26603
9.5%
u 25179
9.0%
n 23357
8.4%
i 22701
8.1%
J 20321
7.3%
r 12600
 
4.5%
L 11464
 
4.1%
Other values (20) 36481
13.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 279522
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 42069
15.1%
v 31785
11.4%
l 26962
9.6%
a 26603
9.5%
u 25179
9.0%
n 23357
8.4%
i 22701
8.1%
J 20321
7.3%
r 12600
 
4.5%
L 11464
 
4.1%
Other values (20) 36481
13.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 279522
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 42069
15.1%
v 31785
11.4%
l 26962
9.6%
a 26603
9.5%
u 25179
9.0%
n 23357
8.4%
i 22701
8.1%
J 20321
7.3%
r 12600
 
4.5%
L 11464
 
4.1%
Other values (20) 36481
13.1%

reproductiveCondition
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

caste
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

behavior
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

vitality
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

establishmentMeans
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

degreeOfEstablishment
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

pathway
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

georeferenceVerificationStatus
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

occurrenceStatus
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:58.832496image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4089407
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESENT
2nd rowPRESENT
3rd rowPRESENT
4th rowPRESENT
5th rowPRESENT
ValueCountFrequency (%)
present 584201
100.0%
2025-01-07T10:48:58.922521image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 1168402
28.6%
P 584201
14.3%
R 584201
14.3%
S 584201
14.3%
N 584201
14.3%
T 584201
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4089407
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 1168402
28.6%
P 584201
14.3%
R 584201
14.3%
S 584201
14.3%
N 584201
14.3%
T 584201
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4089407
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 1168402
28.6%
P 584201
14.3%
R 584201
14.3%
S 584201
14.3%
N 584201
14.3%
T 584201
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4089407
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 1168402
28.6%
P 584201
14.3%
R 584201
14.3%
S 584201
14.3%
N 584201
14.3%
T 584201
14.3%
Distinct31
Distinct (%)< 0.1%
Missing5684
Missing (%)1.0%
Memory size4.5 MiB
2025-01-07T10:48:58.971023image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length53
Median length7
Mean length7.117061383
Min length3

Characters and Unicode

Total characters4117341
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowEthanol
2nd rowEthanol; Histological Material
3rd rowEthanol; Dry
4th rowEthanol
5th rowEthanol
ValueCountFrequency (%)
ethanol 553871
93.4%
dry 13058
 
2.2%
formalin 8143
 
1.4%
cleared 4474
 
0.8%
and 4474
 
0.8%
stained 4474
 
0.8%
histological 2058
 
0.3%
material 2058
 
0.3%
photograph 126
 
< 0.1%
sem 3
 
< 0.1%
2025-01-07T10:48:59.075646image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 581736
14.1%
l 572662
13.9%
n 570962
13.9%
o 566382
13.8%
t 562587
13.7%
h 554123
13.5%
E 553874
13.5%
r 27859
 
0.7%
i 18791
 
0.5%
e 15480
 
0.4%
Other values (16) 92885
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4117341
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 581736
14.1%
l 572662
13.9%
n 570962
13.9%
o 566382
13.8%
t 562587
13.7%
h 554123
13.5%
E 553874
13.5%
r 27859
 
0.7%
i 18791
 
0.5%
e 15480
 
0.4%
Other values (16) 92885
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4117341
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 581736
14.1%
l 572662
13.9%
n 570962
13.9%
o 566382
13.8%
t 562587
13.7%
h 554123
13.5%
E 553874
13.5%
r 27859
 
0.7%
i 18791
 
0.5%
e 15480
 
0.4%
Other values (16) 92885
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4117341
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 581736
14.1%
l 572662
13.9%
n 570962
13.9%
o 566382
13.8%
t 562587
13.7%
h 554123
13.5%
E 553874
13.5%
r 27859
 
0.7%
i 18791
 
0.5%
e 15480
 
0.4%
Other values (16) 92885
 
2.3%

disposition
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

associatedOccurrences
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

associatedReferences
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

associatedSequences
Text

Missing 

Distinct719
Distinct (%)99.7%
Missing583480
Missing (%)99.9%
Memory size4.5 MiB
2025-01-07T10:48:59.148940image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length699
Median length99
Mean length112.1983356
Min length49

Characters and Unicode

Total characters80895
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique717 ?
Unique (%)99.4%

Sample

1st rowhttps://www.ncbi.nlm.nih.gov/gquery?term=AF199141;https://www.ncbi.nlm.nih.gov/gquery?term=AF199204
2nd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=OM928184;https://www.ncbi.nlm.nih.gov/gquery?term=OM943246
3rd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JQ914700
4th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=FJ613461
5th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=FJ766602;https://www.ncbi.nlm.nih.gov/gquery?term=FJ784443
ValueCountFrequency (%)
https://www.ncbi.nlm.nih.gov/gquery?term=jn112709;https://www.ncbi.nlm.nih.gov/gquery?term=jn112771;https://www.ncbi.nlm.nih.gov/gquery?term=jn112642 2
 
0.3%
https://www.ncbi.nlm.nih.gov/gquery?term=ay604497 2
 
0.3%
https://www.ncbi.nlm.nih.gov/gquery?term=jq914700 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj613461 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj766602;https://www.ncbi.nlm.nih.gov/gquery?term=fj784443 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=ay843606;https://www.ncbi.nlm.nih.gov/gquery?term=ay843830;https://www.ncbi.nlm.nih.gov/gquery?term=ay844583;https://www.ncbi.nlm.nih.gov/gquery?term=ay844396;https://www.ncbi.nlm.nih.gov/gquery?term=ay844227 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj766586;https://www.ncbi.nlm.nih.gov/gquery?term=fj784580 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=jq914698 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj766778;https://www.ncbi.nlm.nih.gov/gquery?term=fj784548 1
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj766829;https://www.ncbi.nlm.nih.gov/gquery?term=fj784465 1
 
0.1%
Other values (709) 709
98.3%
2025-01-07T10:48:59.279135image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6533
 
8.1%
/ 4896
 
6.1%
t 4896
 
6.1%
n 4896
 
6.1%
w 4896
 
6.1%
h 3264
 
4.0%
m 3264
 
4.0%
g 3264
 
4.0%
r 3264
 
4.0%
e 3264
 
4.0%
Other values (45) 38458
47.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 80895
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 6533
 
8.1%
/ 4896
 
6.1%
t 4896
 
6.1%
n 4896
 
6.1%
w 4896
 
6.1%
h 3264
 
4.0%
m 3264
 
4.0%
g 3264
 
4.0%
r 3264
 
4.0%
e 3264
 
4.0%
Other values (45) 38458
47.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 80895
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 6533
 
8.1%
/ 4896
 
6.1%
t 4896
 
6.1%
n 4896
 
6.1%
w 4896
 
6.1%
h 3264
 
4.0%
m 3264
 
4.0%
g 3264
 
4.0%
r 3264
 
4.0%
e 3264
 
4.0%
Other values (45) 38458
47.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 80895
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 6533
 
8.1%
/ 4896
 
6.1%
t 4896
 
6.1%
n 4896
 
6.1%
w 4896
 
6.1%
h 3264
 
4.0%
m 3264
 
4.0%
g 3264
 
4.0%
r 3264
 
4.0%
e 3264
 
4.0%
Other values (45) 38458
47.5%

associatedTaxa
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

otherCatalogNumbers
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

occurrenceRemarks
Text

Missing 

Distinct5339
Distinct (%)20.1%
Missing557618
Missing (%)95.4%
Memory size4.5 MiB
2025-01-07T10:48:59.472659image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1294
Median length381
Mean length66.70947598
Min length3

Characters and Unicode

Total characters1773338
Distinct characters91
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3351 ?
Unique (%)12.6%

Sample

1st rowCollected from vegetation removal plot (Cocolob 2) in coastal strand Cocolobo uvifera forest, ca. 10 m inland from beach.
2nd rowCollected in roadside ditch in gum/bay swamp. Water depth: 10-40 cm.
3rd rowComplete clutch of eggs removed from the ovaries of a female (Total Length: 57 inches) collected along wooded road.
4th rowCollected on surface at night.
5th rowCollected above and below the falls, south of the creek.
ValueCountFrequency (%)
collected 21028
 
7.1%
in 15429
 
5.2%
of 11658
 
3.9%
the 11088
 
3.7%
on 10611
 
3.6%
from 7596
 
2.6%
and 5597
 
1.9%
at 5284
 
1.8%
area 4127
 
1.4%
road 4049
 
1.4%
Other values (6088) 200792
67.5%
2025-01-07T10:48:59.747388image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270676
15.3%
e 160711
 
9.1%
o 140496
 
7.9%
a 114427
 
6.5%
t 108900
 
6.1%
l 98347
 
5.5%
n 89158
 
5.0%
r 81415
 
4.6%
d 76949
 
4.3%
i 72320
 
4.1%
Other values (81) 559939
31.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1773338
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
270676
15.3%
e 160711
 
9.1%
o 140496
 
7.9%
a 114427
 
6.5%
t 108900
 
6.1%
l 98347
 
5.5%
n 89158
 
5.0%
r 81415
 
4.6%
d 76949
 
4.3%
i 72320
 
4.1%
Other values (81) 559939
31.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1773338
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
270676
15.3%
e 160711
 
9.1%
o 140496
 
7.9%
a 114427
 
6.5%
t 108900
 
6.1%
l 98347
 
5.5%
n 89158
 
5.0%
r 81415
 
4.6%
d 76949
 
4.3%
i 72320
 
4.1%
Other values (81) 559939
31.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1773338
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
270676
15.3%
e 160711
 
9.1%
o 140496
 
7.9%
a 114427
 
6.5%
t 108900
 
6.1%
l 98347
 
5.5%
n 89158
 
5.0%
r 81415
 
4.6%
d 76949
 
4.3%
i 72320
 
4.1%
Other values (81) 559939
31.6%

organismID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

organismName
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

organismScope
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

associatedOrganisms
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

previousIdentifications
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

organismRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

materialEntityID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

materialEntityRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

verbatimLabel
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

materialSampleID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

eventID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

parentEventID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

eventType
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

fieldNumber
Text

Missing 

Distinct2
Distinct (%)25.0%
Missing584193
Missing (%)> 99.9%
Memory size4.5 MiB
2025-01-07T10:48:59.799819image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.125
Min length6

Characters and Unicode

Total characters49
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)12.5%

Sample

1st row83-012
2nd row83-012
3rd row83-012
4th row83-012
5th row83-012
ValueCountFrequency (%)
83-012 7
87.5%
83-024a 1
 
12.5%
2025-01-07T10:48:59.894131image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 8
16.3%
3 8
16.3%
- 8
16.3%
0 8
16.3%
2 8
16.3%
1 7
14.3%
4 1
 
2.0%
A 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8 8
16.3%
3 8
16.3%
- 8
16.3%
0 8
16.3%
2 8
16.3%
1 7
14.3%
4 1
 
2.0%
A 1
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8 8
16.3%
3 8
16.3%
- 8
16.3%
0 8
16.3%
2 8
16.3%
1 7
14.3%
4 1
 
2.0%
A 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8 8
16.3%
3 8
16.3%
- 8
16.3%
0 8
16.3%
2 8
16.3%
1 7
14.3%
4 1
 
2.0%
A 1
 
2.0%

eventDate
Text

Missing 

Distinct31039
Distinct (%)5.7%
Missing39140
Missing (%)6.7%
Memory size4.5 MiB
2025-01-07T10:49:00.096094image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length9.940764428
Min length4

Characters and Unicode

Total characters5418323
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7117 ?
Unique (%)1.3%

Sample

1st row1972-02-01/1972-02-03
2nd row1971-09-03
3rd row1992-10-15
4th row1992-06-24
5th row1998-09-03
ValueCountFrequency (%)
1883 739
 
0.1%
1973-09-22 723
 
0.1%
1935 701
 
0.1%
1998-10-09 690
 
0.1%
1971-08-16 610
 
0.1%
1940 598
 
0.1%
1966-04-11 579
 
0.1%
1970-06-19 564
 
0.1%
1976-10-03 540
 
0.1%
1971-07-31 521
 
0.1%
Other values (31029) 538796
98.9%
2025-01-07T10:49:00.359658image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1054903
19.5%
1 987143
18.2%
0 809873
14.9%
9 731463
13.5%
2 355880
 
6.6%
7 294421
 
5.4%
6 287515
 
5.3%
8 286448
 
5.3%
3 210910
 
3.9%
5 208423
 
3.8%
Other values (2) 191344
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5418323
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 1054903
19.5%
1 987143
18.2%
0 809873
14.9%
9 731463
13.5%
2 355880
 
6.6%
7 294421
 
5.4%
6 287515
 
5.3%
8 286448
 
5.3%
3 210910
 
3.9%
5 208423
 
3.8%
Other values (2) 191344
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5418323
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 1054903
19.5%
1 987143
18.2%
0 809873
14.9%
9 731463
13.5%
2 355880
 
6.6%
7 294421
 
5.4%
6 287515
 
5.3%
8 286448
 
5.3%
3 210910
 
3.9%
5 208423
 
3.8%
Other values (2) 191344
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5418323
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 1054903
19.5%
1 987143
18.2%
0 809873
14.9%
9 731463
13.5%
2 355880
 
6.6%
7 294421
 
5.4%
6 287515
 
5.3%
8 286448
 
5.3%
3 210910
 
3.9%
5 208423
 
3.8%
Other values (2) 191344
 
3.5%

eventTime
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

startDayOfYear
Real number (ℝ)

Missing 

Distinct366
Distinct (%)0.1%
Missing86170
Missing (%)14.8%
Infinite0
Infinite (%)0.0%
Mean178.1293293
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:00.437446image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile37
Q1111
median178
Q3239
95-th percentile321
Maximum366
Range365
Interquartile range (IQR)128

Descriptive statistics

Standard deviation85.90071781
Coefficient of variation (CV)0.4822379232
Kurtosis-0.7841562207
Mean178.1293293
Median Absolute Deviation (MAD)64
Skewness0.05039449496
Sum88713928
Variance7378.933321
MonotonicityNot monotonic
2025-01-07T10:49:00.587594image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
227 2917
 
0.5%
230 2852
 
0.5%
233 2687
 
0.5%
196 2660
 
0.5%
210 2604
 
0.4%
232 2592
 
0.4%
145 2504
 
0.4%
106 2489
 
0.4%
228 2467
 
0.4%
209 2408
 
0.4%
Other values (356) 471851
80.8%
(Missing) 86170
 
14.8%
ValueCountFrequency (%)
1 921
0.2%
2 481
0.1%
3 408
0.1%
4 617
0.1%
5 572
0.1%
ValueCountFrequency (%)
366 90
 
< 0.1%
365 419
0.1%
364 372
0.1%
363 351
0.1%
362 533
0.1%

endDayOfYear
Real number (ℝ)

Missing 

Distinct366
Distinct (%)0.1%
Missing86170
Missing (%)14.8%
Infinite0
Infinite (%)0.0%
Mean178.0753527
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:00.649782image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile37
Q1112
median178
Q3239
95-th percentile321
Maximum366
Range365
Interquartile range (IQR)127

Descriptive statistics

Standard deviation85.74069844
Coefficient of variation (CV)0.4814854899
Kurtosis-0.7836090776
Mean178.0753527
Median Absolute Deviation (MAD)64
Skewness0.05092198979
Sum88687046
Variance7351.46737
MonotonicityNot monotonic
2025-01-07T10:49:00.712414image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 3038
 
0.5%
227 2924
 
0.5%
233 2713
 
0.5%
196 2664
 
0.5%
210 2658
 
0.5%
232 2593
 
0.4%
145 2544
 
0.4%
226 2520
 
0.4%
228 2516
 
0.4%
209 2373
 
0.4%
Other values (356) 471488
80.7%
(Missing) 86170
 
14.8%
ValueCountFrequency (%)
1 920
0.2%
2 396
0.1%
3 429
0.1%
4 606
0.1%
5 579
0.1%
ValueCountFrequency (%)
366 101
 
< 0.1%
365 513
0.1%
364 424
0.1%
363 363
0.1%
362 553
0.1%

year
Real number (ℝ)

Missing 

Distinct184
Distinct (%)< 0.1%
Missing39600
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean1964.694512
Minimum1817
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:00.773924image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1817
5-th percentile1905
Q11959
median1970
Q31981
95-th percentile1997
Maximum2022
Range205
Interquartile range (IQR)22

Descriptive statistics

Standard deviation26.41728557
Coefficient of variation (CV)0.01344600161
Kurtosis1.658012599
Mean1964.694512
Median Absolute Deviation (MAD)11
Skewness-1.236860341
Sum1069974596
Variance697.872977
MonotonicityNot monotonic
2025-01-07T10:49:00.830487image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1971 16999
 
2.9%
1966 15984
 
2.7%
1969 15769
 
2.7%
1970 15631
 
2.7%
1976 15292
 
2.6%
1980 15179
 
2.6%
1979 14958
 
2.6%
1972 14412
 
2.5%
1961 12797
 
2.2%
1984 12646
 
2.2%
Other values (174) 394934
67.6%
(Missing) 39600
 
6.8%
ValueCountFrequency (%)
1817 1
 
< 0.1%
1822 1
 
< 0.1%
1830 1
 
< 0.1%
1838 4
< 0.1%
1839 4
< 0.1%
ValueCountFrequency (%)
2022 1
 
< 0.1%
2020 2
 
< 0.1%
2019 440
0.1%
2018 266
 
< 0.1%
2017 700
0.1%

month
Real number (ℝ)

Missing 

Distinct12
Distinct (%)< 0.1%
Missing59025
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean6.360244946
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:00.881166image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6
Q38
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.825063292
Coefficient of variation (CV)0.4441752347
Kurtosis-0.7860663087
Mean6.360244946
Median Absolute Deviation (MAD)2
Skewness0.05532792523
Sum3340248
Variance7.980982602
MonotonicityNot monotonic
2025-01-07T10:49:00.928269image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 67450
11.5%
5 63954
10.9%
7 63917
10.9%
6 59064
10.1%
4 55219
9.5%
3 46402
7.9%
10 42862
7.3%
9 36546
6.3%
11 25432
 
4.4%
2 25273
 
4.3%
Other values (2) 39057
6.7%
(Missing) 59025
10.1%
ValueCountFrequency (%)
1 21593
 
3.7%
2 25273
 
4.3%
3 46402
7.9%
4 55219
9.5%
5 63954
10.9%
ValueCountFrequency (%)
12 17464
 
3.0%
11 25432
 
4.4%
10 42862
7.3%
9 36546
6.3%
8 67450
11.5%

day
Real number (ℝ)

Missing 

Distinct31
Distinct (%)< 0.1%
Missing100844
Missing (%)17.3%
Infinite0
Infinite (%)0.0%
Mean15.85330305
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:00.977777image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.700549959
Coefficient of variation (CV)0.5488162268
Kurtosis-1.162355803
Mean15.85330305
Median Absolute Deviation (MAD)7
Skewness-0.01338186456
Sum7662805
Variance75.69956959
MonotonicityNot monotonic
2025-01-07T10:49:01.030736image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
15 18907
 
3.2%
13 17259
 
3.0%
21 17015
 
2.9%
25 16944
 
2.9%
19 16843
 
2.9%
24 16667
 
2.9%
16 16371
 
2.8%
3 16363
 
2.8%
22 16276
 
2.8%
28 16272
 
2.8%
Other values (21) 314440
53.8%
(Missing) 100844
 
17.3%
ValueCountFrequency (%)
1 15353
2.6%
2 14447
2.5%
3 16363
2.8%
4 14084
2.4%
5 15753
2.7%
ValueCountFrequency (%)
31 8822
1.5%
30 14840
2.5%
29 14375
2.5%
28 16272
2.8%
27 15407
2.6%
Distinct42558
Distinct (%)7.3%
Missing51
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:49:01.218631image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length194
Median length11
Mean length12.14387743
Min length4

Characters and Unicode

Total characters7093846
Distinct characters74
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14192 ?
Unique (%)2.4%

Sample

1st row01-03 February 1972
2nd row3 Sep 1971
3rd row-- --- ----
4th row15 Oct 1992; 09:05-13:00 hrs
5th row24 Jun 1992; 10:30-11:40 hrs
ValueCountFrequency (%)
173374
 
9.4%
may 65316
 
3.5%
aug 63760
 
3.5%
jul 58386
 
3.2%
jun 53770
 
2.9%
apr 50984
 
2.8%
mar 43098
 
2.3%
oct 40349
 
2.2%
sep 34295
 
1.9%
hrs 24306
 
1.3%
Other values (3264) 1238022
67.1%
2025-01-07T10:49:01.501893image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1261510
17.8%
1 874532
 
12.3%
9 688315
 
9.7%
- 499756
 
7.0%
2 328876
 
4.6%
0 243409
 
3.4%
6 227222
 
3.2%
7 227024
 
3.2%
8 217953
 
3.1%
u 208644
 
2.9%
Other values (64) 2316605
32.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7093846
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1261510
17.8%
1 874532
 
12.3%
9 688315
 
9.7%
- 499756
 
7.0%
2 328876
 
4.6%
0 243409
 
3.4%
6 227222
 
3.2%
7 227024
 
3.2%
8 217953
 
3.1%
u 208644
 
2.9%
Other values (64) 2316605
32.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7093846
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1261510
17.8%
1 874532
 
12.3%
9 688315
 
9.7%
- 499756
 
7.0%
2 328876
 
4.6%
0 243409
 
3.4%
6 227222
 
3.2%
7 227024
 
3.2%
8 217953
 
3.1%
u 208644
 
2.9%
Other values (64) 2316605
32.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7093846
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1261510
17.8%
1 874532
 
12.3%
9 688315
 
9.7%
- 499756
 
7.0%
2 328876
 
4.6%
0 243409
 
3.4%
6 227222
 
3.2%
7 227024
 
3.2%
8 217953
 
3.1%
u 208644
 
2.9%
Other values (64) 2316605
32.7%

habitat
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

samplingProtocol
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

sampleSizeValue
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

sampleSizeUnit
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

samplingEffort
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

fieldNotes
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

eventRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

locationID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

higherGeographyID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB
Distinct6286
Distinct (%)1.1%
Missing4414
Missing (%)0.8%
Memory size4.5 MiB
2025-01-07T10:49:01.692754image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length167
Median length118
Mean length48.81643259
Min length4

Characters and Unicode

Total characters28303133
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1092 ?
Unique (%)0.2%

Sample

1st rowOceania, Papua New Guinea, Central Province, Kairuku-Hiri District, New Guinea
2nd rowNorth America, United States, North Carolina, Buncombe - Yancey
3rd rowOceania, Pacific Ocean , Tonga, Tonga Islands, Tongatapu Island Group, Tonga Islands
4th rowNorth America, Grenada, St. George Parish, Lesser Antilles, Windward Islands, Grenada Island
5th rowNorth America, United States, Virginia, Augusta
ValueCountFrequency (%)
america 483266
 
12.9%
north 476209
 
12.7%
states 351020
 
9.4%
united 349359
 
9.4%
virginia 96173
 
2.6%
south 71896
 
1.9%
islands 71471
 
1.9%
carolina 61728
 
1.7%
54664
 
1.5%
asia 39306
 
1.1%
Other values (4622) 1680221
45.0%
2025-01-07T10:49:01.955526image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3155526
 
11.1%
a 2668328
 
9.4%
i 2176293
 
7.7%
e 2119779
 
7.5%
t 1973350
 
7.0%
r 1844062
 
6.5%
, 1669519
 
5.9%
n 1511861
 
5.3%
o 1298349
 
4.6%
s 1011828
 
3.6%
Other values (73) 8874238
31.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28303133
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3155526
 
11.1%
a 2668328
 
9.4%
i 2176293
 
7.7%
e 2119779
 
7.5%
t 1973350
 
7.0%
r 1844062
 
6.5%
, 1669519
 
5.9%
n 1511861
 
5.3%
o 1298349
 
4.6%
s 1011828
 
3.6%
Other values (73) 8874238
31.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28303133
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3155526
 
11.1%
a 2668328
 
9.4%
i 2176293
 
7.7%
e 2119779
 
7.5%
t 1973350
 
7.0%
r 1844062
 
6.5%
, 1669519
 
5.9%
n 1511861
 
5.3%
o 1298349
 
4.6%
s 1011828
 
3.6%
Other values (73) 8874238
31.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28303133
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3155526
 
11.1%
a 2668328
 
9.4%
i 2176293
 
7.7%
e 2119779
 
7.5%
t 1973350
 
7.0%
r 1844062
 
6.5%
, 1669519
 
5.9%
n 1511861
 
5.3%
o 1298349
 
4.6%
s 1011828
 
3.6%
Other values (73) 8874238
31.4%

continent
Text

Missing 

Distinct6
Distinct (%)< 0.1%
Missing10069
Missing (%)1.7%
Memory size4.5 MiB
2025-01-07T10:49:02.015094image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length11.7863662
Min length4

Characters and Unicode

Total characters6766930
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOCEANIA
2nd rowNORTH_AMERICA
3rd rowOCEANIA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 416962
72.6%
south_america 64731
 
11.3%
asia 39723
 
6.9%
oceania 29733
 
5.2%
africa 20601
 
3.6%
europe 2382
 
0.4%
2025-01-07T10:49:02.113913image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1143500
16.9%
R 921638
13.6%
I 571750
8.4%
C 532027
7.9%
E 516190
7.6%
O 513808
7.6%
H 481693
7.1%
T 481693
7.1%
_ 481693
7.1%
M 481693
7.1%
Other values (5) 641245
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6766930
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1143500
16.9%
R 921638
13.6%
I 571750
8.4%
C 532027
7.9%
E 516190
7.6%
O 513808
7.6%
H 481693
7.1%
T 481693
7.1%
_ 481693
7.1%
M 481693
7.1%
Other values (5) 641245
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6766930
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1143500
16.9%
R 921638
13.6%
I 571750
8.4%
C 532027
7.9%
E 516190
7.6%
O 513808
7.6%
H 481693
7.1%
T 481693
7.1%
_ 481693
7.1%
M 481693
7.1%
Other values (5) 641245
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6766930
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1143500
16.9%
R 921638
13.6%
I 571750
8.4%
C 532027
7.9%
E 516190
7.6%
O 513808
7.6%
H 481693
7.1%
T 481693
7.1%
_ 481693
7.1%
M 481693
7.1%
Other values (5) 641245
9.5%

waterBody
Text

Missing 

Distinct3
Distinct (%)< 0.1%
Missing555994
Missing (%)95.2%
Memory size4.5 MiB
2025-01-07T10:49:02.158270image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length13
Mean length12.96972383
Min length12

Characters and Unicode

Total characters365837
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPacific Ocean
2nd rowPacific Ocean
3rd rowPacific Ocean
4th rowPacific Ocean
5th rowIndian Ocean
ValueCountFrequency (%)
ocean 28207
50.0%
pacific 26665
47.3%
indian 1198
 
2.1%
atlantic 344
 
0.6%
2025-01-07T10:49:02.261306image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 81881
22.4%
a 56414
15.4%
i 54872
15.0%
n 30947
 
8.5%
O 28207
 
7.7%
28207
 
7.7%
e 28207
 
7.7%
P 26665
 
7.3%
f 26665
 
7.3%
I 1198
 
0.3%
Other values (4) 2574
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 365837
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 81881
22.4%
a 56414
15.4%
i 54872
15.0%
n 30947
 
8.5%
O 28207
 
7.7%
28207
 
7.7%
e 28207
 
7.7%
P 26665
 
7.3%
f 26665
 
7.3%
I 1198
 
0.3%
Other values (4) 2574
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 365837
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 81881
22.4%
a 56414
15.4%
i 54872
15.0%
n 30947
 
8.5%
O 28207
 
7.7%
28207
 
7.7%
e 28207
 
7.7%
P 26665
 
7.3%
f 26665
 
7.3%
I 1198
 
0.3%
Other values (4) 2574
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 365837
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 81881
22.4%
a 56414
15.4%
i 54872
15.0%
n 30947
 
8.5%
O 28207
 
7.7%
28207
 
7.7%
e 28207
 
7.7%
P 26665
 
7.3%
f 26665
 
7.3%
I 1198
 
0.3%
Other values (4) 2574
 
0.7%

islandGroup
Text

Missing 

Distinct41
Distinct (%)0.2%
Missing564324
Missing (%)96.6%
Memory size4.5 MiB
2025-01-07T10:49:02.333849image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length25
Mean length13.3327967
Min length10

Characters and Unicode

Total characters265016
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowWindward Islands
2nd rowVirgin Islands
3rd rowHispaniola
4th rowHispaniola
5th rowGreater Sunda Islands
ValueCountFrequency (%)
islands 10225
31.0%
hispaniola 8927
27.1%
virgin 2527
 
7.7%
windward 2377
 
7.2%
bahama 1504
 
4.6%
leeward 1357
 
4.1%
sunda 1019
 
3.1%
greater 1018
 
3.1%
northern 671
 
2.0%
solomon 655
 
2.0%
Other values (48) 2663
 
8.1%
2025-01-07T10:49:02.461884image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 41073
15.5%
s 30081
11.4%
n 27407
10.3%
i 26949
10.2%
l 20663
 
7.8%
d 17902
 
6.8%
13066
 
4.9%
o 12195
 
4.6%
r 10747
 
4.1%
I 10283
 
3.9%
Other values (35) 54650
20.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 265016
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 41073
15.5%
s 30081
11.4%
n 27407
10.3%
i 26949
10.2%
l 20663
 
7.8%
d 17902
 
6.8%
13066
 
4.9%
o 12195
 
4.6%
r 10747
 
4.1%
I 10283
 
3.9%
Other values (35) 54650
20.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 265016
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 41073
15.5%
s 30081
11.4%
n 27407
10.3%
i 26949
10.2%
l 20663
 
7.8%
d 17902
 
6.8%
13066
 
4.9%
o 12195
 
4.6%
r 10747
 
4.1%
I 10283
 
3.9%
Other values (35) 54650
20.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 265016
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 41073
15.5%
s 30081
11.4%
n 27407
10.3%
i 26949
10.2%
l 20663
 
7.8%
d 17902
 
6.8%
13066
 
4.9%
o 12195
 
4.6%
r 10747
 
4.1%
I 10283
 
3.9%
Other values (35) 54650
20.6%

island
Text

Missing 

Distinct39
Distinct (%)0.5%
Missing576136
Missing (%)98.6%
Memory size4.5 MiB
2025-01-07T10:49:02.538862image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length10
Mean length10.77445753
Min length6

Characters and Unicode

Total characters86896
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st rowNew Guinea
2nd rowGrenada Island
3rd rowNew Guinea
4th rowNew Guinea
5th rowLittle Swan Island
ValueCountFrequency (%)
new 4350
29.0%
guinea 4350
29.0%
island 1306
 
8.7%
borneo 712
 
4.7%
bougainville 652
 
4.3%
sumatra 558
 
3.7%
okinawa 493
 
3.3%
grenada 267
 
1.8%
isla 258
 
1.7%
swan 241
 
1.6%
Other values (44) 1803
12.0%
2025-01-07T10:49:02.676762image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11374
13.1%
a 10388
12.0%
n 8928
10.3%
6925
 
8.0%
i 6731
 
7.7%
u 5716
 
6.6%
w 5086
 
5.9%
G 4959
 
5.7%
N 4459
 
5.1%
l 3060
 
3.5%
Other values (34) 19270
22.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 86896
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 11374
13.1%
a 10388
12.0%
n 8928
10.3%
6925
 
8.0%
i 6731
 
7.7%
u 5716
 
6.6%
w 5086
 
5.9%
G 4959
 
5.7%
N 4459
 
5.1%
l 3060
 
3.5%
Other values (34) 19270
22.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 86896
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 11374
13.1%
a 10388
12.0%
n 8928
10.3%
6925
 
8.0%
i 6731
 
7.7%
u 5716
 
6.6%
w 5086
 
5.9%
G 4959
 
5.7%
N 4459
 
5.1%
l 3060
 
3.5%
Other values (34) 19270
22.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 86896
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 11374
13.1%
a 10388
12.0%
n 8928
10.3%
6925
 
8.0%
i 6731
 
7.7%
u 5716
 
6.6%
w 5086
 
5.9%
G 4959
 
5.7%
N 4459
 
5.1%
l 3060
 
3.5%
Other values (34) 19270
22.2%

countryCode
Text

Missing 

Distinct198
Distinct (%)< 0.1%
Missing10837
Missing (%)1.9%
Memory size4.5 MiB
2025-01-07T10:49:02.846339image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1146728
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowPG
2nd rowUS
3rd rowTO
4th rowGD
5th rowUS
ValueCountFrequency (%)
us 334216
58.3%
mx 22787
 
4.0%
ec 16235
 
2.8%
br 14722
 
2.6%
pe 12875
 
2.2%
ph 11392
 
2.0%
hn 10938
 
1.9%
pa 7718
 
1.3%
jm 7293
 
1.3%
gu 5665
 
1.0%
Other values (188) 129523
 
22.6%
2025-01-07T10:49:03.060666image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 348407
30.4%
S 342999
29.9%
P 50905
 
4.4%
M 48558
 
4.2%
C 41150
 
3.6%
E 38991
 
3.4%
H 32407
 
2.8%
G 25767
 
2.2%
R 24403
 
2.1%
X 22787
 
2.0%
Other values (16) 170354
14.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1146728
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 348407
30.4%
S 342999
29.9%
P 50905
 
4.4%
M 48558
 
4.2%
C 41150
 
3.6%
E 38991
 
3.4%
H 32407
 
2.8%
G 25767
 
2.2%
R 24403
 
2.1%
X 22787
 
2.0%
Other values (16) 170354
14.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1146728
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 348407
30.4%
S 342999
29.9%
P 50905
 
4.4%
M 48558
 
4.2%
C 41150
 
3.6%
E 38991
 
3.4%
H 32407
 
2.8%
G 25767
 
2.2%
R 24403
 
2.1%
X 22787
 
2.0%
Other values (16) 170354
14.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1146728
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 348407
30.4%
S 342999
29.9%
P 50905
 
4.4%
M 48558
 
4.2%
C 41150
 
3.6%
E 38991
 
3.4%
H 32407
 
2.8%
G 25767
 
2.2%
R 24403
 
2.1%
X 22787
 
2.0%
Other values (16) 170354
14.9%

stateProvince
Text

Missing 

Distinct2059
Distinct (%)0.4%
Missing17001
Missing (%)2.9%
Memory size4.5 MiB
2025-01-07T10:49:03.345048image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length69
Median length52
Mean length10.58665021
Min length3

Characters and Unicode

Total characters6004748
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique356 ?
Unique (%)0.1%

Sample

1st rowCentral Province
2nd rowNorth Carolina
3rd rowTonga Islands
4th rowSt. George Parish
5th rowVirginia
ValueCountFrequency (%)
virginia 93314
 
11.0%
carolina 61709
 
7.2%
north 57614
 
6.8%
maryland 32649
 
3.8%
province 27443
 
3.2%
pennsylvania 18911
 
2.2%
west 18140
 
2.1%
florida 18100
 
2.1%
island 18015
 
2.1%
tennessee 17444
 
2.0%
Other values (1937) 487863
57.3%
2025-01-07T10:49:03.608348image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 826291
13.8%
i 632216
 
10.5%
n 557794
 
9.3%
r 474453
 
7.9%
o 407390
 
6.8%
e 304504
 
5.1%
284002
 
4.7%
l 264922
 
4.4%
s 256173
 
4.3%
t 191100
 
3.2%
Other values (62) 1805903
30.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6004748
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 826291
13.8%
i 632216
 
10.5%
n 557794
 
9.3%
r 474453
 
7.9%
o 407390
 
6.8%
e 304504
 
5.1%
284002
 
4.7%
l 264922
 
4.4%
s 256173
 
4.3%
t 191100
 
3.2%
Other values (62) 1805903
30.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6004748
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 826291
13.8%
i 632216
 
10.5%
n 557794
 
9.3%
r 474453
 
7.9%
o 407390
 
6.8%
e 304504
 
5.1%
284002
 
4.7%
l 264922
 
4.4%
s 256173
 
4.3%
t 191100
 
3.2%
Other values (62) 1805903
30.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6004748
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 826291
13.8%
i 632216
 
10.5%
n 557794
 
9.3%
r 474453
 
7.9%
o 407390
 
6.8%
e 304504
 
5.1%
284002
 
4.7%
l 264922
 
4.4%
s 256173
 
4.3%
t 191100
 
3.2%
Other values (62) 1805903
30.1%

county
Text

Missing 

Distinct3056
Distinct (%)0.8%
Missing191557
Missing (%)32.8%
Memory size4.5 MiB
2025-01-07T10:49:03.819329image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length56
Median length43
Mean length9.394395432
Min length3

Characters and Unicode

Total characters3688653
Distinct characters74
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique504 ?
Unique (%)0.1%

Sample

1st rowKairuku-Hiri District
2nd rowBuncombe - Yancey
3rd rowTongatapu Island Group
4th rowAugusta
5th rowElko
ValueCountFrequency (%)
21119
 
3.8%
island 14180
 
2.6%
swain 12742
 
2.3%
city 8568
 
1.6%
province 8458
 
1.5%
giles 8024
 
1.5%
frederick 7508
 
1.4%
macon 7377
 
1.3%
municipality 7367
 
1.3%
haywood 7297
 
1.3%
Other values (2826) 448585
81.4%
2025-01-07T10:49:04.087837image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 361375
 
9.8%
e 318401
 
8.6%
n 281913
 
7.6%
o 250126
 
6.8%
i 237836
 
6.4%
r 221961
 
6.0%
l 181195
 
4.9%
158581
 
4.3%
s 154891
 
4.2%
t 142082
 
3.9%
Other values (64) 1380292
37.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3688653
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 361375
 
9.8%
e 318401
 
8.6%
n 281913
 
7.6%
o 250126
 
6.8%
i 237836
 
6.4%
r 221961
 
6.0%
l 181195
 
4.9%
158581
 
4.3%
s 154891
 
4.2%
t 142082
 
3.9%
Other values (64) 1380292
37.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3688653
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 361375
 
9.8%
e 318401
 
8.6%
n 281913
 
7.6%
o 250126
 
6.8%
i 237836
 
6.4%
r 221961
 
6.0%
l 181195
 
4.9%
158581
 
4.3%
s 154891
 
4.2%
t 142082
 
3.9%
Other values (64) 1380292
37.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3688653
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 361375
 
9.8%
e 318401
 
8.6%
n 281913
 
7.6%
o 250126
 
6.8%
i 237836
 
6.4%
r 221961
 
6.0%
l 181195
 
4.9%
158581
 
4.3%
s 154891
 
4.2%
t 142082
 
3.9%
Other values (64) 1380292
37.4%

municipality
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB
Distinct56242
Distinct (%)9.7%
Missing2303
Missing (%)0.4%
Memory size4.5 MiB
2025-01-07T10:49:04.293072image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length295
Median length193
Mean length54.40064066
Min length2

Characters and Unicode

Total characters31655624
Distinct characters110
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24789 ?
Unique (%)4.3%

Sample

1st rowKairuku, Yule Island
2nd rowPisgah National Forest, near Cane River Gap
3rd rowNo Locality Data
4th rowTongatapu Island, adjacent to Fua'amotu Airport
5th rowGrand Anse Bay, west end of, along road to jetty just east of base of Quarantine Point
ValueCountFrequency (%)
of 456712
 
8.0%
mi 190409
 
3.3%
road 182915
 
3.2%
route 156226
 
2.7%
on 147202
 
2.6%
national 106083
 
1.8%
by 93415
 
1.6%
forest 89661
 
1.6%
junction 81776
 
1.4%
km 68711
 
1.2%
Other values (30771) 4165761
72.6%
2025-01-07T10:49:04.569097image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5156973
16.3%
a 2389818
 
7.5%
o 2384544
 
7.5%
e 1748111
 
5.5%
n 1666496
 
5.3%
i 1568945
 
5.0%
t 1523016
 
4.8%
r 1291111
 
4.1%
l 964589
 
3.0%
, 845140
 
2.7%
Other values (100) 12116881
38.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 31655624
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5156973
16.3%
a 2389818
 
7.5%
o 2384544
 
7.5%
e 1748111
 
5.5%
n 1666496
 
5.3%
i 1568945
 
5.0%
t 1523016
 
4.8%
r 1291111
 
4.1%
l 964589
 
3.0%
, 845140
 
2.7%
Other values (100) 12116881
38.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 31655624
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5156973
16.3%
a 2389818
 
7.5%
o 2384544
 
7.5%
e 1748111
 
5.5%
n 1666496
 
5.3%
i 1568945
 
5.0%
t 1523016
 
4.8%
r 1291111
 
4.1%
l 964589
 
3.0%
, 845140
 
2.7%
Other values (100) 12116881
38.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 31655624
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5156973
16.3%
a 2389818
 
7.5%
o 2384544
 
7.5%
e 1748111
 
5.5%
n 1666496
 
5.3%
i 1568945
 
5.0%
t 1523016
 
4.8%
r 1291111
 
4.1%
l 964589
 
3.0%
, 845140
 
2.7%
Other values (100) 12116881
38.3%

verbatimLocality
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

verbatimElevation
Text

Missing 

Distinct2882
Distinct (%)1.1%
Missing331608
Missing (%)56.8%
Memory size4.5 MiB
2025-01-07T10:49:04.758108image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length93
Median length46
Mean length7.093015246
Min length3

Characters and Unicode

Total characters1791646
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique530 ?
Unique (%)0.2%

Sample

1st row4320 ft
2nd row4351 ft
3rd row2200 m
4th row30-50 m
5th row30 ft
ValueCountFrequency (%)
ft 191831
36.8%
m 59860
 
11.5%
ca 13358
 
2.6%
1100-1350 4058
 
0.8%
200 3781
 
0.7%
10 3450
 
0.7%
3400 2848
 
0.5%
3500 2819
 
0.5%
20 2706
 
0.5%
3600 2513
 
0.5%
Other values (2009) 234300
44.9%
2025-01-07T10:49:05.005105image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 376273
21.0%
268931
15.0%
t 192412
10.7%
f 192004
10.7%
1 99566
 
5.6%
3 96808
 
5.4%
2 90988
 
5.1%
4 83319
 
4.7%
5 76675
 
4.3%
m 59946
 
3.3%
Other values (47) 254724
14.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1791646
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 376273
21.0%
268931
15.0%
t 192412
10.7%
f 192004
10.7%
1 99566
 
5.6%
3 96808
 
5.4%
2 90988
 
5.1%
4 83319
 
4.7%
5 76675
 
4.3%
m 59946
 
3.3%
Other values (47) 254724
14.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1791646
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 376273
21.0%
268931
15.0%
t 192412
10.7%
f 192004
10.7%
1 99566
 
5.6%
3 96808
 
5.4%
2 90988
 
5.1%
4 83319
 
4.7%
5 76675
 
4.3%
m 59946
 
3.3%
Other values (47) 254724
14.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1791646
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 376273
21.0%
268931
15.0%
t 192412
10.7%
f 192004
10.7%
1 99566
 
5.6%
3 96808
 
5.4%
2 90988
 
5.1%
4 83319
 
4.7%
5 76675
 
4.3%
m 59946
 
3.3%
Other values (47) 254724
14.2%

verticalDatum
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

verbatimDepth
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

minimumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

maximumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

locationAccordingTo
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

locationRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

decimalLatitude
Real number (ℝ)

Missing 

Distinct24490
Distinct (%)5.8%
Missing162667
Missing (%)27.8%
Infinite0
Infinite (%)0.0%
Mean26.42285253
Minimum-55.9442
Maximum72.3394
Zeros44
Zeros (%)< 0.1%
Negative58991
Negative (%)10.1%
Memory size4.5 MiB
2025-01-07T10:49:05.081558image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-55.9442
5-th percentile-12.83
Q116.7374649
median35.5775
Q338.4122066
95-th percentile41.3258
Maximum72.3394
Range128.2836
Interquartile range (IQR)21.6747417

Descriptive statistics

Standard deviation18.03353823
Coefficient of variation (CV)0.6824977815
Kurtosis0.7643295732
Mean26.42285253
Median Absolute Deviation (MAD)3.7310621
Skewness-1.361025016
Sum11138130.72
Variance325.2085011
MonotonicityNot monotonic
2025-01-07T10:49:05.145593image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39.6306 4296
 
0.7%
13.6389 2247
 
0.4%
39.8872 1888
 
0.3%
-12.83 1754
 
0.3%
26.9844 1718
 
0.3%
-4.0147 1664
 
0.3%
37.4161 1535
 
0.3%
36.7631 1511
 
0.3%
25.4017 1483
 
0.3%
36.9486 1468
 
0.3%
Other values (24480) 401970
68.8%
(Missing) 162667
27.8%
ValueCountFrequency (%)
-55.9442 1
 
< 0.1%
-50.7 2
 
< 0.1%
-50 5
< 0.1%
-48.9667 1
 
< 0.1%
-45.9092 2
 
< 0.1%
ValueCountFrequency (%)
72.3394 2
 
< 0.1%
66.9871 1
 
< 0.1%
66.89 1
 
< 0.1%
66.3594 11
< 0.1%
66.02 2
 
< 0.1%

decimalLongitude
Real number (ℝ)

Missing 

Distinct24797
Distinct (%)5.9%
Missing162667
Missing (%)27.8%
Infinite0
Infinite (%)0.0%
Mean-65.50031942
Minimum-179.867
Maximum179.98
Zeros1
Zeros (%)< 0.1%
Negative382134
Negative (%)65.4%
Memory size4.5 MiB
2025-01-07T10:49:05.204593image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-179.867
5-th percentile-112.251
Q1-83.4200528
median-79.4033
Q3-76.2176
95-th percentile99.9583
Maximum179.98
Range359.847
Interquartile range (IQR)7.2024528

Descriptive statistics

Standard deviation55.97500731
Coefficient of variation (CV)-0.8545760967
Kurtosis7.277313441
Mean-65.50031942
Median Absolute Deviation (MAD)3.8231
Skewness2.752262713
Sum-27610611.65
Variance3133.201443
MonotonicityNot monotonic
2025-01-07T10:49:05.264697image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-77.4714 4296
 
0.7%
144.962 2247
 
0.4%
-77.7786 2139
 
0.4%
-87.1889 1888
 
0.3%
-69.28 1763
 
0.3%
-81.4919 1718
 
0.3%
-80.5097 1653
 
0.3%
-81.2228 1509
 
0.3%
-80.6567 1483
 
0.3%
-79.5561 1463
 
0.3%
Other values (24787) 401375
68.7%
(Missing) 162667
27.8%
ValueCountFrequency (%)
-179.867 36
< 0.1%
-179.25 1
 
< 0.1%
-178.7 55
< 0.1%
-178.68 20
 
< 0.1%
-178.333 7
 
< 0.1%
ValueCountFrequency (%)
179.98 46
< 0.1%
179.756 68
< 0.1%
179.43 61
< 0.1%
179.4 1
 
< 0.1%
179.38 7
 
< 0.1%

coordinateUncertaintyInMeters
Real number (ℝ)

Missing  Skewed 

Distinct7350
Distinct (%)5.1%
Missing439218
Missing (%)75.2%
Infinite0
Infinite (%)0.0%
Mean8065.639111
Minimum0.05
Maximum3884420
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:05.327962image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile160.93
Q1910.89
median2607.14
Q35703
95-th percentile28363.1
Maximum3884420
Range3884419.95
Interquartile range (IQR)4792.11

Descriptive statistics

Standard deviation38151.05974
Coefficient of variation (CV)4.730072746
Kurtosis1420.560477
Mean8065.639111
Median Absolute Deviation (MAD)2018.12
Skewness27.97550952
Sum1169380555
Variance1455503359
MonotonicityNot monotonic
2025-01-07T10:49:05.394010image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
347.62 1384
 
0.2%
186.68 1338
 
0.2%
4615 1110
 
0.2%
5615 1066
 
0.2%
1066 1030
 
0.2%
3615 978
 
0.2%
5115 953
 
0.2%
4115 946
 
0.2%
177.03 882
 
0.2%
402.34 826
 
0.1%
Other values (7340) 134470
 
23.0%
(Missing) 439218
75.2%
ValueCountFrequency (%)
0.05 61
< 0.1%
1.02 30
< 0.1%
3 1
 
< 0.1%
3.29 1
 
< 0.1%
4 6
 
< 0.1%
ValueCountFrequency (%)
3884420 1
 
< 0.1%
2175860 3
 
< 0.1%
2101020 1
 
< 0.1%
1501015 8
< 0.1%
1465107 2
 
< 0.1%

coordinatePrecision
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

pointRadiusSpatialFit
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

verbatimCoordinateSystem
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

verbatimSRS
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

footprintWKT
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

footprintSRS
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

footprintSpatialFit
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

georeferencedBy
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

georeferencedDate
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

georeferenceProtocol
Text

Missing 

Distinct3371
Distinct (%)2.3%
Missing439136
Missing (%)75.2%
Memory size4.5 MiB
2025-01-07T10:49:05.585911image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length302
Median length251
Mean length91.26128977
Min length3

Characters and Unicode

Total characters13238819
Distinct characters86
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique891 ?
Unique (%)0.6%

Sample

1st rowUSGS Palo Alto Quad (TopoZone - 1:24,000), MaNIS/HerpNET/ORNIS Georeferencing Guidelines
2nd rowTerrain Navigator v. 5.03 USGS 1:24,000, MaNIS/HerpNET/ORNIS Georeferencing Guidelines
3rd rowAlexandria Digital Library Gazetteer, MaNIS/HerpNET/ORNIS Georeferencing Guidelines
4th rowUSGS Chesterfield Quad (TopoZine - 1:24,000), MaNIS/HerpNET/ORNIS Georeferencing Guidelines
5th rowUSGS Falls Church Quad (TopoZone - 1:24,000), MaNIS/HerpNET/ORNIS Georeferencing Guidelines
ValueCountFrequency (%)
georeferencing 134216
 
9.7%
manis/herpnet/ornis 134163
 
9.7%
guidelines 134143
 
9.7%
usgs 59079
 
4.3%
1:24,000 54333
 
3.9%
44136
 
3.2%
quad 39827
 
2.9%
digital 22588
 
1.6%
gazetteer 22105
 
1.6%
topozone 21638
 
1.6%
Other values (3792) 715459
51.8%
2025-01-07T10:49:05.851865image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1320173
 
10.0%
1236622
 
9.3%
r 733799
 
5.5%
i 691510
 
5.2%
a 629206
 
4.8%
n 622138
 
4.7%
o 500801
 
3.8%
N 461182
 
3.5%
S 454207
 
3.4%
G 414644
 
3.1%
Other values (76) 6174537
46.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13238819
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1320173
 
10.0%
1236622
 
9.3%
r 733799
 
5.5%
i 691510
 
5.2%
a 629206
 
4.8%
n 622138
 
4.7%
o 500801
 
3.8%
N 461182
 
3.5%
S 454207
 
3.4%
G 414644
 
3.1%
Other values (76) 6174537
46.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13238819
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1320173
 
10.0%
1236622
 
9.3%
r 733799
 
5.5%
i 691510
 
5.2%
a 629206
 
4.8%
n 622138
 
4.7%
o 500801
 
3.8%
N 461182
 
3.5%
S 454207
 
3.4%
G 414644
 
3.1%
Other values (76) 6174537
46.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13238819
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1320173
 
10.0%
1236622
 
9.3%
r 733799
 
5.5%
i 691510
 
5.2%
a 629206
 
4.8%
n 622138
 
4.7%
o 500801
 
3.8%
N 461182
 
3.5%
S 454207
 
3.4%
G 414644
 
3.1%
Other values (76) 6174537
46.6%

georeferenceSources
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

georeferenceRemarks
Text

Missing 

Distinct3681
Distinct (%)2.6%
Missing443625
Missing (%)75.9%
Memory size4.5 MiB
2025-01-07T10:49:06.038677image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length83
Median length55
Mean length22.53162702
Min length7

Characters and Unicode

Total characters3167406
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1057 ?
Unique (%)0.8%

Sample

1st rowLocality extent = 0.05
2nd rowLocality extent = 95
3rd rowLocality extent = 3.5
4th rowDatum Guam 63
5th rowLocality extent = 1.08
ValueCountFrequency (%)
extent 134257
22.0%
134207
22.0%
locality 134203
22.0%
mi 40072
 
6.6%
km 8736
 
1.4%
0.1 7251
 
1.2%
datum 6200
 
1.0%
63 5497
 
0.9%
guam 5494
 
0.9%
1 5323
 
0.9%
Other values (2938) 128798
21.1%
2025-01-07T10:49:06.295742image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
469462
14.8%
t 411232
13.0%
e 269464
 
8.5%
i 175099
 
5.5%
. 149589
 
4.7%
a 146541
 
4.6%
l 134689
 
4.3%
n 134567
 
4.2%
o 134447
 
4.2%
y 134376
 
4.2%
Other values (54) 1007940
31.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3167406
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
469462
14.8%
t 411232
13.0%
e 269464
 
8.5%
i 175099
 
5.5%
. 149589
 
4.7%
a 146541
 
4.6%
l 134689
 
4.3%
n 134567
 
4.2%
o 134447
 
4.2%
y 134376
 
4.2%
Other values (54) 1007940
31.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3167406
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
469462
14.8%
t 411232
13.0%
e 269464
 
8.5%
i 175099
 
5.5%
. 149589
 
4.7%
a 146541
 
4.6%
l 134689
 
4.3%
n 134567
 
4.2%
o 134447
 
4.2%
y 134376
 
4.2%
Other values (54) 1007940
31.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3167406
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
469462
14.8%
t 411232
13.0%
e 269464
 
8.5%
i 175099
 
5.5%
. 149589
 
4.7%
a 146541
 
4.6%
l 134689
 
4.3%
n 134567
 
4.2%
o 134447
 
4.2%
y 134376
 
4.2%
Other values (54) 1007940
31.8%

geologicalContextID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

earliestEonOrLowestEonothem
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

latestEonOrHighestEonothem
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

earliestEraOrLowestErathem
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

latestEraOrHighestErathem
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

earliestPeriodOrLowestSystem
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

latestPeriodOrHighestSystem
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

earliestEpochOrLowestSeries
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

latestEpochOrHighestSeries
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

earliestAgeOrLowestStage
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

latestAgeOrHighestStage
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

lowestBiostratigraphicZone
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

highestBiostratigraphicZone
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

lithostratigraphicTerms
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

group
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

formation
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

member
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

bed
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

identificationID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

verbatimIdentification
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB
Distinct3
Distinct (%)0.7%
Missing583784
Missing (%)99.9%
Memory size4.5 MiB
2025-01-07T10:49:06.348894image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.167865707
Min length3

Characters and Unicode

Total characters1321
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowaff.
2nd rowcf.
3rd rowcf.
4th rowcf.
5th rowcf.
ValueCountFrequency (%)
cf 382
91.6%
aff 28
 
6.7%
uncertain 7
 
1.7%
2025-01-07T10:49:06.445288image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 438
33.2%
. 410
31.0%
c 389
29.4%
a 35
 
2.6%
n 14
 
1.1%
u 7
 
0.5%
e 7
 
0.5%
r 7
 
0.5%
t 7
 
0.5%
i 7
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1321
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
f 438
33.2%
. 410
31.0%
c 389
29.4%
a 35
 
2.6%
n 14
 
1.1%
u 7
 
0.5%
e 7
 
0.5%
r 7
 
0.5%
t 7
 
0.5%
i 7
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1321
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
f 438
33.2%
. 410
31.0%
c 389
29.4%
a 35
 
2.6%
n 14
 
1.1%
u 7
 
0.5%
e 7
 
0.5%
r 7
 
0.5%
t 7
 
0.5%
i 7
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1321
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
f 438
33.2%
. 410
31.0%
c 389
29.4%
a 35
 
2.6%
n 14
 
1.1%
u 7
 
0.5%
e 7
 
0.5%
r 7
 
0.5%
t 7
 
0.5%
i 7
 
0.5%

typeStatus
Text

Missing 

Distinct6
Distinct (%)< 0.1%
Missing571070
Missing (%)97.8%
Memory size4.5 MiB
2025-01-07T10:49:06.492013image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.014698043
Min length7

Characters and Unicode

Total characters105241
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPARATYPE
2nd rowPARATYPE
3rd rowPARATYPE
4th rowPARATYPE
5th rowPARALECTOTYPE
ValueCountFrequency (%)
paratype 10832
82.5%
holotype 1222
 
9.3%
syntype 835
 
6.4%
paralectotype 208
 
1.6%
neotype 23
 
0.2%
lectotype 11
 
0.1%
2025-01-07T10:49:06.663252image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 24171
23.0%
A 22080
21.0%
Y 13966
13.3%
E 13373
12.7%
T 13350
12.7%
R 11040
10.5%
O 2686
 
2.6%
L 1441
 
1.4%
H 1222
 
1.2%
N 858
 
0.8%
Other values (2) 1054
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 105241
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
P 24171
23.0%
A 22080
21.0%
Y 13966
13.3%
E 13373
12.7%
T 13350
12.7%
R 11040
10.5%
O 2686
 
2.6%
L 1441
 
1.4%
H 1222
 
1.2%
N 858
 
0.8%
Other values (2) 1054
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 105241
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
P 24171
23.0%
A 22080
21.0%
Y 13966
13.3%
E 13373
12.7%
T 13350
12.7%
R 11040
10.5%
O 2686
 
2.6%
L 1441
 
1.4%
H 1222
 
1.2%
N 858
 
0.8%
Other values (2) 1054
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 105241
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
P 24171
23.0%
A 22080
21.0%
Y 13966
13.3%
E 13373
12.7%
T 13350
12.7%
R 11040
10.5%
O 2686
 
2.6%
L 1441
 
1.4%
H 1222
 
1.2%
N 858
 
0.8%
Other values (2) 1054
 
1.0%

identifiedBy
Text

Missing 

Distinct8
Distinct (%)10.5%
Missing584125
Missing (%)> 99.9%
Memory size4.5 MiB
2025-01-07T10:49:06.737352image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length122
Median length18
Mean length25.17105263
Min length14

Characters and Unicode

Total characters1913
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)5.3%

Sample

1st rowGower, David, (BMNH), The Natural History Museum (UNITED KINGDOM)
2nd rowCrombie, Ronald I.
3rd rowCrombie, Ronald I.
4th rowCrombie, Ronald I.
5th rowCrombie, Ronald I.
ValueCountFrequency (%)
ronald 56
18.7%
crombie 55
18.3%
i 55
18.3%
natural 11
 
3.7%
museum 11
 
3.7%
united 11
 
3.7%
history 11
 
3.7%
gower 10
 
3.3%
the 10
 
3.3%
bmnh 10
 
3.3%
Other values (26) 60
20.0%
2025-01-07T10:49:06.863634image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
224
 
11.7%
o 146
 
7.6%
e 102
 
5.3%
r 99
 
5.2%
, 98
 
5.1%
a 95
 
5.0%
i 87
 
4.5%
I 77
 
4.0%
d 73
 
3.8%
n 73
 
3.8%
Other values (39) 839
43.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1913
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
224
 
11.7%
o 146
 
7.6%
e 102
 
5.3%
r 99
 
5.2%
, 98
 
5.1%
a 95
 
5.0%
i 87
 
4.5%
I 77
 
4.0%
d 73
 
3.8%
n 73
 
3.8%
Other values (39) 839
43.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1913
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
224
 
11.7%
o 146
 
7.6%
e 102
 
5.3%
r 99
 
5.2%
, 98
 
5.1%
a 95
 
5.0%
i 87
 
4.5%
I 77
 
4.0%
d 73
 
3.8%
n 73
 
3.8%
Other values (39) 839
43.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1913
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
224
 
11.7%
o 146
 
7.6%
e 102
 
5.3%
r 99
 
5.2%
, 98
 
5.1%
a 95
 
5.0%
i 87
 
4.5%
I 77
 
4.0%
d 73
 
3.8%
n 73
 
3.8%
Other values (39) 839
43.9%

identifiedByID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

dateIdentified
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

identificationReferences
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

identificationVerificationStatus
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

identificationRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

taxonID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

scientificNameID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

acceptedNameUsageID
Real number (ℝ)

Distinct8475
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3607990.362
Minimum1
Maximum12221705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:06.929712image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2424089
Q12431224
median2431517
Q34287413
95-th percentile9296806
Maximum12221705
Range12221704
Interquartile range (IQR)1856189

Descriptive statistics

Standard deviation2307431.631
Coefficient of variation (CV)0.6395337568
Kurtosis2.347415633
Mean3607990.362
Median Absolute Deviation (MAD)4883
Skewness1.867361173
Sum2.107791577 × 1012
Variance5.32424073 × 1012
MonotonicityNot monotonic
2025-01-07T10:49:06.994363image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2431491 75714
 
13.0%
2431539 13092
 
2.2%
2431224 10146
 
1.7%
2431506 9986
 
1.7%
2431516 8012
 
1.4%
2431529 7074
 
1.2%
2431489 6103
 
1.0%
2431484 5929
 
1.0%
2431219 4681
 
0.8%
2431510 4614
 
0.8%
Other values (8465) 438850
75.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
44 198
< 0.1%
775 1
 
< 0.1%
952 366
0.1%
953 12
 
< 0.1%
ValueCountFrequency (%)
12221705 1
 
< 0.1%
11815352 413
0.1%
11804395 1
 
< 0.1%
11632221 1
 
< 0.1%
11554463 3
 
< 0.1%

parentNameUsageID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

originalNameUsageID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

nameAccordingToID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

namePublishedInID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

taxonConceptID
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB
Distinct9012
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:07.169105image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length182
Median length112
Mean length35.63831969
Min length5

Characters and Unicode

Total characters20819942
Distinct characters88
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1713 ?
Unique (%)0.3%

Sample

1st rowCarlia bicarinata (Macleay, 1877)
2nd rowPlethodon montanus Highton & Peabody, 2000
3rd rowEnhydris enhydris (Schneider, 1799)
4th rowGehyra mutilata (Wiegmann, 1834)
5th rowAnolis richardii Duméril & Bibron, 1837
ValueCountFrequency (%)
plethodon 168423
 
6.7%
green 95287
 
3.8%
1818 93378
 
3.7%
81423
 
3.2%
cinereus 75774
 
3.0%
desmognathus 35846
 
1.4%
cope 33117
 
1.3%
duméril 26833
 
1.1%
linnaeus 26096
 
1.0%
bibron 23820
 
0.9%
Other values (8722) 1859231
73.8%
2025-01-07T10:49:07.438935image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1935027
 
9.3%
e 1567127
 
7.5%
o 1187336
 
5.7%
n 1168671
 
5.6%
a 1154833
 
5.5%
i 1117013
 
5.4%
s 1062494
 
5.1%
r 1046115
 
5.0%
t 861966
 
4.1%
l 827376
 
4.0%
Other values (78) 8891984
42.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20819942
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1935027
 
9.3%
e 1567127
 
7.5%
o 1187336
 
5.7%
n 1168671
 
5.6%
a 1154833
 
5.5%
i 1117013
 
5.4%
s 1062494
 
5.1%
r 1046115
 
5.0%
t 861966
 
4.1%
l 827376
 
4.0%
Other values (78) 8891984
42.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20819942
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1935027
 
9.3%
e 1567127
 
7.5%
o 1187336
 
5.7%
n 1168671
 
5.6%
a 1154833
 
5.5%
i 1117013
 
5.4%
s 1062494
 
5.1%
r 1046115
 
5.0%
t 861966
 
4.1%
l 827376
 
4.0%
Other values (78) 8891984
42.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20819942
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1935027
 
9.3%
e 1567127
 
7.5%
o 1187336
 
5.7%
n 1168671
 
5.6%
a 1154833
 
5.5%
i 1117013
 
5.4%
s 1062494
 
5.1%
r 1046115
 
5.0%
t 861966
 
4.1%
l 827376
 
4.0%
Other values (78) 8891984
42.7%

acceptedNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

parentNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

originalNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

nameAccordingTo
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

namePublishedIn
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

namePublishedInYear
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB
Distinct167
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:49:07.628692image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length86
Median length82
Mean length66.44007265
Min length10

Characters and Unicode

Total characters38814224
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia, Chordata, Vertebrata, Reptilia, Squamata, Sauria, Scincidae, Eugongylinae
2nd rowAnimalia, Chordata, Vertebrata, Amphibia, Caudata, Plethodontidae
3rd rowAnimalia, Chordata, Vertebrata, Reptilia, Squamata, Ophidia, Homalopsinae
4th rowAnimalia, Chordata, Vertebrata, Reptilia, Squamata, Sauria, Gekkoninae
5th rowAnimalia, Chordata, Vertebrata, Reptilia, Squamata, Sauria, Polychrotinae
ValueCountFrequency (%)
animalia 584195
15.7%
vertebrata 584195
15.7%
chordata 584178
15.7%
amphibia 395159
10.6%
caudata 237127
6.4%
plethodontidae 221369
 
5.9%
reptilia 189036
 
5.1%
squamata 169309
 
4.5%
anura 157511
 
4.2%
sauria 116154
 
3.1%
Other values (166) 484544
13.0%
2025-01-07T10:49:07.885200image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 6566805
16.9%
i 3313617
 
8.5%
3138578
 
8.1%
, 3138578
 
8.1%
t 3000106
 
7.7%
e 2360956
 
6.1%
r 2244920
 
5.8%
d 1648115
 
4.2%
h 1357195
 
3.5%
n 1355739
 
3.5%
Other values (36) 10689615
27.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38814224
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 6566805
16.9%
i 3313617
 
8.5%
3138578
 
8.1%
, 3138578
 
8.1%
t 3000106
 
7.7%
e 2360956
 
6.1%
r 2244920
 
5.8%
d 1648115
 
4.2%
h 1357195
 
3.5%
n 1355739
 
3.5%
Other values (36) 10689615
27.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38814224
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 6566805
16.9%
i 3313617
 
8.5%
3138578
 
8.1%
, 3138578
 
8.1%
t 3000106
 
7.7%
e 2360956
 
6.1%
r 2244920
 
5.8%
d 1648115
 
4.2%
h 1357195
 
3.5%
n 1355739
 
3.5%
Other values (36) 10689615
27.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38814224
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 6566805
16.9%
i 3313617
 
8.5%
3138578
 
8.1%
, 3138578
 
8.1%
t 3000106
 
7.7%
e 2360956
 
6.1%
r 2244920
 
5.8%
d 1648115
 
4.2%
h 1357195
 
3.5%
n 1355739
 
3.5%
Other values (36) 10689615
27.5%

kingdom
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:07.934202image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4673608
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 584201
100.0%
2025-01-07T10:49:08.021582image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1168402
25.0%
i 1168402
25.0%
n 584201
12.5%
A 584201
12.5%
m 584201
12.5%
l 584201
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4673608
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1168402
25.0%
i 1168402
25.0%
n 584201
12.5%
A 584201
12.5%
m 584201
12.5%
l 584201
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4673608
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1168402
25.0%
i 1168402
25.0%
n 584201
12.5%
A 584201
12.5%
m 584201
12.5%
l 584201
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4673608
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1168402
25.0%
i 1168402
25.0%
n 584201
12.5%
A 584201
12.5%
m 584201
12.5%
l 584201
12.5%

phylum
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:49:08.061094image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4673568
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowChordata
2nd rowChordata
3rd rowChordata
4th rowChordata
5th rowChordata
ValueCountFrequency (%)
chordata 584196
100.0%
2025-01-07T10:49:08.150620image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1168392
25.0%
h 584196
12.5%
C 584196
12.5%
o 584196
12.5%
r 584196
12.5%
d 584196
12.5%
t 584196
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4673568
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1168392
25.0%
h 584196
12.5%
C 584196
12.5%
o 584196
12.5%
r 584196
12.5%
d 584196
12.5%
t 584196
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4673568
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1168392
25.0%
h 584196
12.5%
C 584196
12.5%
o 584196
12.5%
r 584196
12.5%
d 584196
12.5%
t 584196
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4673568
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1168392
25.0%
h 584196
12.5%
C 584196
12.5%
o 584196
12.5%
r 584196
12.5%
d 584196
12.5%
t 584196
12.5%

class
Text

Distinct5
Distinct (%)< 0.1%
Missing203
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:49:08.194090image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.067606396
Min length8

Characters and Unicode

Total characters4711466
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSquamata
2nd rowAmphibia
3rd rowSquamata
4th rowSquamata
5th rowSquamata
ValueCountFrequency (%)
amphibia 395161
67.7%
squamata 169110
29.0%
testudines 18909
 
3.2%
crocodylia 804
 
0.1%
sphenodontia 14
 
< 0.1%
2025-01-07T10:49:08.298227image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 903309
19.2%
i 810049
17.2%
m 564271
12.0%
h 395175
8.4%
p 395175
8.4%
A 395161
8.4%
b 395161
8.4%
t 188033
 
4.0%
u 188019
 
4.0%
S 169124
 
3.6%
Other values (12) 307989
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4711466
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 903309
19.2%
i 810049
17.2%
m 564271
12.0%
h 395175
8.4%
p 395175
8.4%
A 395161
8.4%
b 395161
8.4%
t 188033
 
4.0%
u 188019
 
4.0%
S 169124
 
3.6%
Other values (12) 307989
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4711466
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 903309
19.2%
i 810049
17.2%
m 564271
12.0%
h 395175
8.4%
p 395175
8.4%
A 395161
8.4%
b 395161
8.4%
t 188033
 
4.0%
u 188019
 
4.0%
S 169124
 
3.6%
Other values (12) 307989
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4711466
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 903309
19.2%
i 810049
17.2%
m 564271
12.0%
h 395175
8.4%
p 395175
8.4%
A 395161
8.4%
b 395161
8.4%
t 188033
 
4.0%
u 188019
 
4.0%
S 169124
 
3.6%
Other values (12) 307989
 
6.5%

order
Text

Missing 

Distinct3
Distinct (%)< 0.1%
Missing189040
Missing (%)32.4%
Memory size4.5 MiB
2025-01-07T10:49:08.341230image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length7
Mean length6.208074683
Min length5

Characters and Unicode

Total characters2453189
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCaudata
2nd rowCaudata
3rd rowAnura
4th rowAnura
5th rowCaudata
ValueCountFrequency (%)
caudata 237129
60.0%
anura 157511
39.9%
gymnophiona 521
 
0.1%
2025-01-07T10:49:08.442166image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 869419
35.4%
u 394640
16.1%
C 237129
 
9.7%
d 237129
 
9.7%
t 237129
 
9.7%
n 158553
 
6.5%
A 157511
 
6.4%
r 157511
 
6.4%
o 1042
 
< 0.1%
y 521
 
< 0.1%
Other values (5) 2605
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2453189
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 869419
35.4%
u 394640
16.1%
C 237129
 
9.7%
d 237129
 
9.7%
t 237129
 
9.7%
n 158553
 
6.5%
A 157511
 
6.4%
r 157511
 
6.4%
o 1042
 
< 0.1%
y 521
 
< 0.1%
Other values (5) 2605
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2453189
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 869419
35.4%
u 394640
16.1%
C 237129
 
9.7%
d 237129
 
9.7%
t 237129
 
9.7%
n 158553
 
6.5%
A 157511
 
6.4%
r 157511
 
6.4%
o 1042
 
< 0.1%
y 521
 
< 0.1%
Other values (5) 2605
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2453189
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 869419
35.4%
u 394640
16.1%
C 237129
 
9.7%
d 237129
 
9.7%
t 237129
 
9.7%
n 158553
 
6.5%
A 157511
 
6.4%
r 157511
 
6.4%
o 1042
 
< 0.1%
y 521
 
< 0.1%
Other values (5) 2605
 
0.1%

superfamily
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

family
Text

Distinct159
Distinct (%)< 0.1%
Missing587
Missing (%)0.1%
Memory size4.5 MiB
2025-01-07T10:49:08.603122image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length19
Mean length12.00749468
Min length6

Characters and Unicode

Total characters7007742
Distinct characters42
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowScincidae
2nd rowPlethodontidae
3rd rowHomalopsidae
4th rowGekkonidae
5th rowDactyloidae
ValueCountFrequency (%)
plethodontidae 221371
37.9%
hylidae 41566
 
7.1%
colubridae 38793
 
6.6%
scincidae 26153
 
4.5%
bufonidae 25125
 
4.3%
ranidae 20333
 
3.5%
dactyloidae 18373
 
3.1%
gekkonidae 17255
 
3.0%
phrynosomatidae 16259
 
2.8%
leptodactylidae 10435
 
1.8%
Other values (149) 147951
25.4%
2025-01-07T10:49:08.837672image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 917602
13.1%
d 865810
12.4%
a 768920
11.0%
o 698920
10.0%
i 662199
9.4%
t 582781
8.3%
l 411564
 
5.9%
n 371028
 
5.3%
h 296650
 
4.2%
P 246994
 
3.5%
Other values (32) 1185274
16.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7007742
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 917602
13.1%
d 865810
12.4%
a 768920
11.0%
o 698920
10.0%
i 662199
9.4%
t 582781
8.3%
l 411564
 
5.9%
n 371028
 
5.3%
h 296650
 
4.2%
P 246994
 
3.5%
Other values (32) 1185274
16.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7007742
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 917602
13.1%
d 865810
12.4%
a 768920
11.0%
o 698920
10.0%
i 662199
9.4%
t 582781
8.3%
l 411564
 
5.9%
n 371028
 
5.3%
h 296650
 
4.2%
P 246994
 
3.5%
Other values (32) 1185274
16.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7007742
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 917602
13.1%
d 865810
12.4%
a 768920
11.0%
o 698920
10.0%
i 662199
9.4%
t 582781
8.3%
l 411564
 
5.9%
n 371028
 
5.3%
h 296650
 
4.2%
P 246994
 
3.5%
Other values (32) 1185274
16.9%

subfamily
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

tribe
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

subtribe
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

genus
Text

Distinct1416
Distinct (%)0.2%
Missing1685
Missing (%)0.3%
Memory size4.5 MiB
2025-01-07T10:49:09.031562image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length16
Mean length9.556288583
Min length3

Characters and Unicode

Total characters5566691
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)< 0.1%

Sample

1st rowCarlia
2nd rowPlethodon
3rd rowEnhydris
4th rowGehyra
5th rowAnolis
ValueCountFrequency (%)
plethodon 168423
28.9%
desmognathus 35846
 
6.2%
anolis 18373
 
3.2%
lithobates 12991
 
2.2%
eleutherodactylus 9948
 
1.7%
anaxyrus 9476
 
1.6%
sceloporus 8824
 
1.5%
emoia 8233
 
1.4%
eurycea 7667
 
1.3%
pseudacris 6800
 
1.2%
Other values (1406) 295935
50.8%
2025-01-07T10:49:09.282128image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 686047
12.3%
e 456061
 
8.2%
t 411539
 
7.4%
s 401007
 
7.2%
l 372079
 
6.7%
h 362493
 
6.5%
a 356491
 
6.4%
n 349007
 
6.3%
d 268142
 
4.8%
i 230506
 
4.1%
Other values (42) 1673319
30.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5566691
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 686047
12.3%
e 456061
 
8.2%
t 411539
 
7.4%
s 401007
 
7.2%
l 372079
 
6.7%
h 362493
 
6.5%
a 356491
 
6.4%
n 349007
 
6.3%
d 268142
 
4.8%
i 230506
 
4.1%
Other values (42) 1673319
30.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5566691
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 686047
12.3%
e 456061
 
8.2%
t 411539
 
7.4%
s 401007
 
7.2%
l 372079
 
6.7%
h 362493
 
6.5%
a 356491
 
6.4%
n 349007
 
6.3%
d 268142
 
4.8%
i 230506
 
4.1%
Other values (42) 1673319
30.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5566691
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 686047
12.3%
e 456061
 
8.2%
t 411539
 
7.4%
s 401007
 
7.2%
l 372079
 
6.7%
h 362493
 
6.5%
a 356491
 
6.4%
n 349007
 
6.3%
d 268142
 
4.8%
i 230506
 
4.1%
Other values (42) 1673319
30.1%
Distinct1357
Distinct (%)0.2%
Missing1685
Missing (%)0.3%
Memory size4.5 MiB
2025-01-07T10:49:09.477721image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length16
Mean length9.513697478
Min length3

Characters and Unicode

Total characters5541881
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)< 0.1%

Sample

1st rowCarlia
2nd rowPlethodon
3rd rowEnhydris
4th rowGehyra
5th rowAnolis
ValueCountFrequency (%)
plethodon 168423
28.9%
desmognathus 35846
 
6.2%
anolis 18333
 
3.1%
lithobates 12991
 
2.2%
eleutherodactylus 9947
 
1.7%
anaxyrus 9476
 
1.6%
sceloporus 8824
 
1.5%
emoia 8211
 
1.4%
eurycea 7626
 
1.3%
pseudacris 6800
 
1.2%
Other values (1347) 296039
50.8%
2025-01-07T10:49:09.740697image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 674207
12.2%
e 453829
 
8.2%
t 411395
 
7.4%
s 399277
 
7.2%
l 371549
 
6.7%
a 364650
 
6.6%
h 357431
 
6.4%
n 345478
 
6.2%
d 268371
 
4.8%
i 236254
 
4.3%
Other values (41) 1659440
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5541881
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 674207
12.2%
e 453829
 
8.2%
t 411395
 
7.4%
s 399277
 
7.2%
l 371549
 
6.7%
a 364650
 
6.6%
h 357431
 
6.4%
n 345478
 
6.2%
d 268371
 
4.8%
i 236254
 
4.3%
Other values (41) 1659440
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5541881
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 674207
12.2%
e 453829
 
8.2%
t 411395
 
7.4%
s 399277
 
7.2%
l 371549
 
6.7%
a 364650
 
6.6%
h 357431
 
6.4%
n 345478
 
6.2%
d 268371
 
4.8%
i 236254
 
4.3%
Other values (41) 1659440
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5541881
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 674207
12.2%
e 453829
 
8.2%
t 411395
 
7.4%
s 399277
 
7.2%
l 371549
 
6.7%
a 364650
 
6.6%
h 357431
 
6.4%
n 345478
 
6.2%
d 268371
 
4.8%
i 236254
 
4.3%
Other values (41) 1659440
29.9%

subgenus
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

infragenericEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

specificEpithet
Text

Missing 

Distinct5069
Distinct (%)0.9%
Missing15011
Missing (%)2.6%
Memory size4.5 MiB
2025-01-07T10:49:09.945118image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length16
Mean length8.818503487
Min length3

Characters and Unicode

Total characters5019404
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique752 ?
Unique (%)0.1%

Sample

1st rowbicarinata
2nd rowmontanus
3rd rowenhydris
4th rowmutilata
5th rowrichardii
ValueCountFrequency (%)
cinereus 75774
 
13.3%
glutinosus 13098
 
2.3%
fuscus 10996
 
1.9%
montanus 10396
 
1.8%
jordani 8582
 
1.5%
metcalfi 6940
 
1.2%
cylindraceus 6103
 
1.1%
carolinensis 5850
 
1.0%
teyahalee 5559
 
1.0%
septentrionalis 4872
 
0.9%
Other values (5059) 421020
74.0%
2025-01-07T10:49:10.209090image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 543995
10.8%
s 515115
10.3%
e 488200
9.7%
a 483269
9.6%
r 401688
8.0%
u 396785
7.9%
n 359600
 
7.2%
c 306019
 
6.1%
t 278310
 
5.5%
o 259596
 
5.2%
Other values (17) 986827
19.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5019404
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 543995
10.8%
s 515115
10.3%
e 488200
9.7%
a 483269
9.6%
r 401688
8.0%
u 396785
7.9%
n 359600
 
7.2%
c 306019
 
6.1%
t 278310
 
5.5%
o 259596
 
5.2%
Other values (17) 986827
19.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5019404
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 543995
10.8%
s 515115
10.3%
e 488200
9.7%
a 483269
9.6%
r 401688
8.0%
u 396785
7.9%
n 359600
 
7.2%
c 306019
 
6.1%
t 278310
 
5.5%
o 259596
 
5.2%
Other values (17) 986827
19.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5019404
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 543995
10.8%
s 515115
10.3%
e 488200
9.7%
a 483269
9.6%
r 401688
8.0%
u 396785
7.9%
n 359600
 
7.2%
c 306019
 
6.1%
t 278310
 
5.5%
o 259596
 
5.2%
Other values (17) 986827
19.7%

infraspecificEpithet
Text

Missing 

Distinct1214
Distinct (%)4.9%
Missing559230
Missing (%)95.7%
Memory size4.5 MiB
2025-01-07T10:49:10.414800image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length14
Mean length9.070041248
Min length3

Characters and Unicode

Total characters226488
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique244 ?
Unique (%)1.0%

Sample

1st rowoccidentalis
2nd rowconsobrinus
3rd rowtrinidadensis
4th rowignigularis
5th rowmetcalfi
ValueCountFrequency (%)
viridescens 1460
 
5.8%
blanchardi 1205
 
4.8%
metcalfi 1072
 
4.3%
fasciata 1043
 
4.2%
elegans 909
 
3.6%
stejnegeri 388
 
1.6%
teyahalee 370
 
1.5%
louisianensis 365
 
1.5%
dorsalis 340
 
1.4%
fuscus 318
 
1.3%
Other values (1204) 17501
70.1%
2025-01-07T10:49:10.680890image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 26514
11.7%
i 26373
11.6%
s 22393
9.9%
e 19932
 
8.8%
n 15025
 
6.6%
r 14301
 
6.3%
l 14245
 
6.3%
t 12449
 
5.5%
c 12257
 
5.4%
u 11424
 
5.0%
Other values (16) 51575
22.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 226488
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 26514
11.7%
i 26373
11.6%
s 22393
9.9%
e 19932
 
8.8%
n 15025
 
6.6%
r 14301
 
6.3%
l 14245
 
6.3%
t 12449
 
5.5%
c 12257
 
5.4%
u 11424
 
5.0%
Other values (16) 51575
22.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 226488
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 26514
11.7%
i 26373
11.6%
s 22393
9.9%
e 19932
 
8.8%
n 15025
 
6.6%
r 14301
 
6.3%
l 14245
 
6.3%
t 12449
 
5.5%
c 12257
 
5.4%
u 11424
 
5.0%
Other values (16) 51575
22.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 226488
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 26514
11.7%
i 26373
11.6%
s 22393
9.9%
e 19932
 
8.8%
n 15025
 
6.6%
r 14301
 
6.3%
l 14245
 
6.3%
t 12449
 
5.5%
c 12257
 
5.4%
u 11424
 
5.0%
Other values (16) 51575
22.8%

cultivarEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB
Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:10.835335image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.079066965
Min length5

Characters and Unicode

Total characters4135598
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowSPECIES
2nd rowSPECIES
3rd rowSPECIES
4th rowSPECIES
5th rowSPECIES
ValueCountFrequency (%)
species 544219
93.2%
subspecies 24970
 
4.3%
genus 13326
 
2.3%
family 1101
 
0.2%
order 379
 
0.1%
phylum 198
 
< 0.1%
class 5
 
< 0.1%
kingdom 2
 
< 0.1%
variety 1
 
< 0.1%
2025-01-07T10:49:10.938882image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 1176684
28.5%
E 1152084
27.9%
I 570293
13.8%
P 569387
13.8%
C 569194
13.8%
U 38494
 
0.9%
B 24970
 
0.6%
G 13328
 
0.3%
N 13328
 
0.3%
L 1304
 
< 0.1%
Other values (11) 6532
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4135598
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 1176684
28.5%
E 1152084
27.9%
I 570293
13.8%
P 569387
13.8%
C 569194
13.8%
U 38494
 
0.9%
B 24970
 
0.6%
G 13328
 
0.3%
N 13328
 
0.3%
L 1304
 
< 0.1%
Other values (11) 6532
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4135598
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 1176684
28.5%
E 1152084
27.9%
I 570293
13.8%
P 569387
13.8%
C 569194
13.8%
U 38494
 
0.9%
B 24970
 
0.6%
G 13328
 
0.3%
N 13328
 
0.3%
L 1304
 
< 0.1%
Other values (11) 6532
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4135598
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 1176684
28.5%
E 1152084
27.9%
I 570293
13.8%
P 569387
13.8%
C 569194
13.8%
U 38494
 
0.9%
B 24970
 
0.6%
G 13328
 
0.3%
N 13328
 
0.3%
L 1304
 
< 0.1%
Other values (11) 6532
 
0.2%

verbatimTaxonRank
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

vernacularName
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

nomenclaturalCode
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:10.984928image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.914724555
Min length7

Characters and Unicode

Total characters4623790
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowACCEPTED
2nd rowACCEPTED
3rd rowACCEPTED
4th rowACCEPTED
5th rowACCEPTED
ValueCountFrequency (%)
accepted 534360
91.5%
synonym 49818
 
8.5%
doubtful 23
 
< 0.1%
2025-01-07T10:49:11.083205image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1068720
23.1%
E 1068720
23.1%
T 534383
11.6%
D 534383
11.6%
A 534360
11.6%
P 534360
11.6%
Y 99636
 
2.2%
N 99636
 
2.2%
O 49841
 
1.1%
S 49818
 
1.1%
Other values (5) 49933
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4623790
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1068720
23.1%
E 1068720
23.1%
T 534383
11.6%
D 534383
11.6%
A 534360
11.6%
P 534360
11.6%
Y 99636
 
2.2%
N 99636
 
2.2%
O 49841
 
1.1%
S 49818
 
1.1%
Other values (5) 49933
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4623790
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1068720
23.1%
E 1068720
23.1%
T 534383
11.6%
D 534383
11.6%
A 534360
11.6%
P 534360
11.6%
Y 99636
 
2.2%
N 99636
 
2.2%
O 49841
 
1.1%
S 49818
 
1.1%
Other values (5) 49933
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4623790
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1068720
23.1%
E 1068720
23.1%
T 534383
11.6%
D 534383
11.6%
A 534360
11.6%
P 534360
11.6%
Y 99636
 
2.2%
N 99636
 
2.2%
O 49841
 
1.1%
S 49818
 
1.1%
Other values (5) 49933
 
1.1%

nomenclaturalStatus
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

taxonRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

datasetKey
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:11.136209image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters21031236
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row821cc27a-e3bb-4bc5-ac34-89ada245069d
2nd row821cc27a-e3bb-4bc5-ac34-89ada245069d
3rd row821cc27a-e3bb-4bc5-ac34-89ada245069d
4th row821cc27a-e3bb-4bc5-ac34-89ada245069d
5th row821cc27a-e3bb-4bc5-ac34-89ada245069d
ValueCountFrequency (%)
821cc27a-e3bb-4bc5-ac34-89ada245069d 584201
100.0%
2025-01-07T10:49:11.237171image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 2336804
11.1%
a 2336804
11.1%
- 2336804
11.1%
2 1752603
8.3%
4 1752603
8.3%
b 1752603
8.3%
8 1168402
 
5.6%
3 1168402
 
5.6%
9 1168402
 
5.6%
d 1168402
 
5.6%
Other values (6) 4089407
19.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21031236
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 2336804
11.1%
a 2336804
11.1%
- 2336804
11.1%
2 1752603
8.3%
4 1752603
8.3%
b 1752603
8.3%
8 1168402
 
5.6%
3 1168402
 
5.6%
9 1168402
 
5.6%
d 1168402
 
5.6%
Other values (6) 4089407
19.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21031236
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 2336804
11.1%
a 2336804
11.1%
- 2336804
11.1%
2 1752603
8.3%
4 1752603
8.3%
b 1752603
8.3%
8 1168402
 
5.6%
3 1168402
 
5.6%
9 1168402
 
5.6%
d 1168402
 
5.6%
Other values (6) 4089407
19.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21031236
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 2336804
11.1%
a 2336804
11.1%
- 2336804
11.1%
2 1752603
8.3%
4 1752603
8.3%
b 1752603
8.3%
8 1168402
 
5.6%
3 1168402
 
5.6%
9 1168402
 
5.6%
d 1168402
 
5.6%
Other values (6) 4089407
19.4%

publishingCountry
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:11.274678image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1168402
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 584201
100.0%
2025-01-07T10:49:11.365254image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 584201
50.0%
S 584201
50.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1168402
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 584201
50.0%
S 584201
50.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1168402
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 584201
50.0%
S 584201
50.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1168402
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 584201
50.0%
S 584201
50.0%
Distinct186736
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:11.509544image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99567957
Min length20

Characters and Unicode

Total characters14018300
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40383 ?
Unique (%)6.9%

Sample

1st row2024-12-02T13:56:06.739Z
2nd row2024-12-02T13:56:08.224Z
3rd row2024-12-02T13:55:56.801Z
4th row2024-12-02T13:59:51.499Z
5th row2024-12-02T13:58:04.592Z
ValueCountFrequency (%)
2024-12-02t13:57:45.601z 17
 
< 0.1%
2024-12-02t13:57:51.135z 16
 
< 0.1%
2024-12-02t13:57:54.221z 16
 
< 0.1%
2024-12-02t13:57:23.249z 16
 
< 0.1%
2024-12-02t13:57:52.847z 16
 
< 0.1%
2024-12-02t13:57:53.169z 15
 
< 0.1%
2024-12-02t13:58:01.663z 15
 
< 0.1%
2024-12-02t13:56:52.538z 15
 
< 0.1%
2024-12-02t13:57:22.814z 15
 
< 0.1%
2024-12-02t13:57:12.319z 15
 
< 0.1%
Other values (186726) 584045
> 99.9%
2025-01-07T10:49:11.726979image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2668002
19.0%
0 1480784
10.6%
1 1472907
10.5%
- 1168402
8.3%
: 1168402
8.3%
4 939301
 
6.7%
5 927875
 
6.6%
3 926225
 
6.6%
T 584201
 
4.2%
Z 584201
 
4.2%
Other values (5) 2098000
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14018300
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2668002
19.0%
0 1480784
10.6%
1 1472907
10.5%
- 1168402
8.3%
: 1168402
8.3%
4 939301
 
6.7%
5 927875
 
6.6%
3 926225
 
6.6%
T 584201
 
4.2%
Z 584201
 
4.2%
Other values (5) 2098000
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14018300
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2668002
19.0%
0 1480784
10.6%
1 1472907
10.5%
- 1168402
8.3%
: 1168402
8.3%
4 939301
 
6.7%
5 927875
 
6.6%
3 926225
 
6.6%
T 584201
 
4.2%
Z 584201
 
4.2%
Other values (5) 2098000
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14018300
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2668002
19.0%
0 1480784
10.6%
1 1472907
10.5%
- 1168402
8.3%
: 1168402
8.3%
4 939301
 
6.7%
5 927875
 
6.6%
3 926225
 
6.6%
T 584201
 
4.2%
Z 584201
 
4.2%
Other values (5) 2098000
15.0%

elevation
Real number (ℝ)

Missing 

Distinct1604
Distinct (%)0.6%
Missing332110
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean752.0057
Minimum-9
Maximum8500
Zeros528
Zeros (%)0.1%
Negative5
Negative (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:49:11.799675image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-9
5-th percentile15
Q1198
median665
Q31158
95-th percentile1775
Maximum8500
Range8509
Interquartile range (IQR)960

Descriptive statistics

Standard deviation644.0691369
Coefficient of variation (CV)0.8564684242
Kurtosis2.557610742
Mean752.0057
Median Absolute Deviation (MAD)480
Skewness1.209458357
Sum189573868.9
Variance414825.0531
MonotonicityNot monotonic
2025-01-07T10:49:11.858188image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1067 4286
 
0.7%
373 4059
 
0.7%
1036 2829
 
0.5%
200 2818
 
0.5%
3 2314
 
0.4%
280 2242
 
0.4%
6 2149
 
0.4%
174 2077
 
0.4%
152 2023
 
0.3%
1146 2023
 
0.3%
Other values (1594) 225271
38.6%
(Missing) 332110
56.8%
ValueCountFrequency (%)
-9 1
 
< 0.1%
-7 3
 
< 0.1%
-3 1
 
< 0.1%
0 528
0.1%
0.1 1
 
< 0.1%
ValueCountFrequency (%)
8500 2
 
< 0.1%
4990 1
 
< 0.1%
4755 1
 
< 0.1%
4724 5
 
< 0.1%
4600 15
< 0.1%

elevationAccuracy
Real number (ℝ)

Missing  Skewed  Zeros 

Distinct136
Distinct (%)0.1%
Missing333288
Missing (%)57.1%
Infinite0
Infinite (%)0.0%
Mean4.685674517
Minimum0
Maximum1752.5
Zeros220652
Zeros (%)37.8%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:11.914570image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile30.5
Maximum1752.5
Range1752.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation22.59037644
Coefficient of variation (CV)4.821157842
Kurtosis1043.695738
Mean4.685674517
Median Absolute Deviation (MAD)0
Skewness20.71091822
Sum1175696.65
Variance510.3251078
MonotonicityNot monotonic
2025-01-07T10:49:11.979126image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 220652
37.8%
38 4866
 
0.8%
30.5 2706
 
0.5%
15 2411
 
0.4%
18 1878
 
0.3%
20 1562
 
0.3%
15.5 1561
 
0.3%
61 1329
 
0.2%
26 989
 
0.2%
12 842
 
0.1%
Other values (126) 12117
 
2.1%
(Missing) 333288
57.1%
ValueCountFrequency (%)
0 220652
37.8%
0.15 1
 
< 0.1%
0.5 110
 
< 0.1%
1 312
 
0.1%
1.5 148
 
< 0.1%
ValueCountFrequency (%)
1752.5 5
< 0.1%
1676.5 1
 
< 0.1%
1218 2
 
< 0.1%
883.5 1
 
< 0.1%
701 5
< 0.1%

depth
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

depthAccuracy
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

distanceFromCentroidInMeters
Real number (ℝ)

Missing 

Distinct146
Distinct (%)5.9%
Missing581727
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean2997.086092
Minimum0
Maximum4973.782789
Zeros42
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:12.044206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile606.2018971
Q11872.412429
median3069.863678
Q34710.482857
95-th percentile4961.494347
Maximum4973.782789
Range4973.782789
Interquartile range (IQR)2838.070429

Descriptive statistics

Standard deviation1492.196289
Coefficient of variation (CV)0.4978823573
Kurtosis-1.30154885
Mean2997.086092
Median Absolute Deviation (MAD)1359.12237
Skewness-0.08031095273
Sum7414790.992
Variance2226649.764
MonotonicityNot monotonic
2025-01-07T10:49:12.108318image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2063.191632 334
 
0.1%
4961.494347 245
 
< 0.1%
1710.741308 132
 
< 0.1%
4852.601363 128
 
< 0.1%
818.121102 83
 
< 0.1%
4878.728947 83
 
< 0.1%
2259.882955 80
 
< 0.1%
1971.013948 69
 
< 0.1%
3977.25588 55
 
< 0.1%
4128.763711 53
 
< 0.1%
Other values (136) 1212
 
0.2%
(Missing) 581727
99.6%
ValueCountFrequency (%)
0 42
< 0.1%
235.3110738 2
 
< 0.1%
347.4636295 15
 
< 0.1%
364.8971997 29
< 0.1%
394.2671276 1
 
< 0.1%
ValueCountFrequency (%)
4973.782789 7
 
< 0.1%
4961.494347 245
< 0.1%
4918.771835 5
 
< 0.1%
4878.728947 83
 
< 0.1%
4874.99087 15
 
< 0.1%

issue
Text

Distinct165
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:49:12.167264image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length186
Median length179
Mean length68.60599385
Min length28

Characters and Unicode

Total characters40079553
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)< 0.1%

Sample

1st rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84
2nd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84
3rd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
4th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;CONTINENT_DERIVED_FROM_COUNTRY;CONTINENT_INVALID
5th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84
ValueCountFrequency (%)
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84 249666
42.7%
occurrence_status_inferred_from_individual_count 227050
38.9%
occurrence_status_inferred_from_individual_count;coordinate_reprojected 34842
 
6.0%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;geodetic_datum_invalid 12098
 
2.1%
occurrence_status_inferred_from_individual_count;continent_derived_from_country;continent_invalid 9004
 
1.5%
occurrence_status_inferred_from_individual_count;country_derived_from_coordinates;country_invalid;geodetic_datum_assumed_wgs84;continent_derived_from_coordinates;continent_invalid 6887
 
1.2%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;continent_derived_from_coordinates;continent_invalid 6809
 
1.2%
occurrence_status_inferred_from_individual_count;taxon_match_higherrank 5451
 
0.9%
occurrence_status_inferred_from_individual_count;country_invalid 5419
 
0.9%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;taxon_match_higherrank 4662
 
0.8%
Other values (155) 22311
 
3.8%
2025-01-07T10:49:12.304678image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 4053596
10.1%
E 3553564
 
8.9%
R 3202871
 
8.0%
U 2974631
 
7.4%
I 2922553
 
7.3%
D 2881308
 
7.2%
C 2865419
 
7.1%
N 2681132
 
6.7%
T 2652470
 
6.6%
O 2377822
 
5.9%
Other values (19) 9914187
24.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 40079553
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
_ 4053596
10.1%
E 3553564
 
8.9%
R 3202871
 
8.0%
U 2974631
 
7.4%
I 2922553
 
7.3%
D 2881308
 
7.2%
C 2865419
 
7.1%
N 2681132
 
6.7%
T 2652470
 
6.6%
O 2377822
 
5.9%
Other values (19) 9914187
24.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 40079553
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
_ 4053596
10.1%
E 3553564
 
8.9%
R 3202871
 
8.0%
U 2974631
 
7.4%
I 2922553
 
7.3%
D 2881308
 
7.2%
C 2865419
 
7.1%
N 2681132
 
6.7%
T 2652470
 
6.6%
O 2377822
 
5.9%
Other values (19) 9914187
24.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 40079553
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
_ 4053596
10.1%
E 3553564
 
8.9%
R 3202871
 
8.0%
U 2974631
 
7.4%
I 2922553
 
7.3%
D 2881308
 
7.2%
C 2865419
 
7.1%
N 2681132
 
6.7%
T 2652470
 
6.6%
O 2377822
 
5.9%
Other values (19) 9914187
24.7%

mediaType
Text

Missing 

Distinct23
Distinct (%)0.4%
Missing579082
Missing (%)99.1%
Memory size4.5 MiB
2025-01-07T10:49:12.365183image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length285
Median length274
Mean length32.18480172
Min length10

Characters and Unicode

Total characters164754
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.1%

Sample

1st rowStillImage;StillImage;StillImage;StillImage;StillImage
2nd rowStillImage;StillImage
3rd rowStillImage;StillImage;StillImage
4th rowStillImage;StillImage;StillImage
5th rowStillImage;StillImage;StillImage;StillImage
ValueCountFrequency (%)
stillimage;stillimage 2352
45.9%
stillimage 841
 
16.4%
stillimage;stillimage;stillimage 690
 
13.5%
stillimage;stillimage;stillimage;stillimage 366
 
7.1%
stillimage;stillimage;stillimage;stillimage;stillimage 268
 
5.2%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 188
 
3.7%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 118
 
2.3%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 110
 
2.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 58
 
1.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 41
 
0.8%
Other values (13) 87
 
1.7%
2025-01-07T10:49:12.485765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 30886
18.7%
S 15443
9.4%
t 15443
9.4%
i 15443
9.4%
I 15443
9.4%
m 15443
9.4%
a 15443
9.4%
g 15443
9.4%
e 15443
9.4%
; 10324
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 164754
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 30886
18.7%
S 15443
9.4%
t 15443
9.4%
i 15443
9.4%
I 15443
9.4%
m 15443
9.4%
a 15443
9.4%
g 15443
9.4%
e 15443
9.4%
; 10324
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 164754
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 30886
18.7%
S 15443
9.4%
t 15443
9.4%
i 15443
9.4%
I 15443
9.4%
m 15443
9.4%
a 15443
9.4%
g 15443
9.4%
e 15443
9.4%
; 10324
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 164754
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 30886
18.7%
S 15443
9.4%
t 15443
9.4%
i 15443
9.4%
I 15443
9.4%
m 15443
9.4%
a 15443
9.4%
g 15443
9.4%
e 15443
9.4%
; 10324
 
6.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size570.6 KiB
True
421534 
False
162667 
ValueCountFrequency (%)
True 421534
72.2%
False 162667
 
27.8%
2025-01-07T10:49:12.540765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

hasGeospatialIssues
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size570.6 KiB
False
581994 
True
 
2207
ValueCountFrequency (%)
False 581994
99.6%
True 2207
 
0.4%
2025-01-07T10:49:12.579278image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

taxonKey
Real number (ℝ)

Distinct9012
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3430990.768
Minimum1
Maximum12386358
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:12.628679image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2424012
Q12431220
median2431513
Q32467928
95-th percentile8960303
Maximum12386358
Range12386357
Interquartile range (IQR)36708

Descriptive statistics

Standard deviation2033259.832
Coefficient of variation (CV)0.5926159437
Kurtosis2.956428027
Mean3430990.768
Median Absolute Deviation (MAD)4579
Skewness1.97108703
Sum2.004388238 × 1012
Variance4.134145544 × 1012
MonotonicityNot monotonic
2025-01-07T10:49:12.694019image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2431491 75714
 
13.0%
2431539 13092
 
2.2%
2431224 10137
 
1.7%
2431506 9986
 
1.7%
2431529 7074
 
1.2%
2431516 6940
 
1.2%
2431489 6103
 
1.0%
2431484 5559
 
1.0%
2431219 4681
 
0.8%
2431510 4614
 
0.8%
Other values (9002) 440301
75.4%
ValueCountFrequency (%)
1 2
 
< 0.1%
44 198
< 0.1%
775 1
 
< 0.1%
952 366
0.1%
953 12
 
< 0.1%
ValueCountFrequency (%)
12386358 1
 
< 0.1%
12378183 8
< 0.1%
12221705 1
 
< 0.1%
11632221 1
 
< 0.1%
11544743 11
< 0.1%

acceptedTaxonKey
Real number (ℝ)

Distinct8475
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3607990.362
Minimum1
Maximum12221705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:12.755526image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2424089
Q12431224
median2431517
Q34287413
95-th percentile9296806
Maximum12221705
Range12221704
Interquartile range (IQR)1856189

Descriptive statistics

Standard deviation2307431.631
Coefficient of variation (CV)0.6395337568
Kurtosis2.347415633
Mean3607990.362
Median Absolute Deviation (MAD)4883
Skewness1.867361173
Sum2.107791577 × 1012
Variance5.32424073 × 1012
MonotonicityNot monotonic
2025-01-07T10:49:12.903658image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2431491 75714
 
13.0%
2431539 13092
 
2.2%
2431224 10146
 
1.7%
2431506 9986
 
1.7%
2431516 8012
 
1.4%
2431529 7074
 
1.2%
2431489 6103
 
1.0%
2431484 5929
 
1.0%
2431219 4681
 
0.8%
2431510 4614
 
0.8%
Other values (8465) 438850
75.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
44 198
< 0.1%
775 1
 
< 0.1%
952 366
0.1%
953 12
 
< 0.1%
ValueCountFrequency (%)
12221705 1
 
< 0.1%
11815352 413
0.1%
11804395 1
 
< 0.1%
11632221 1
 
< 0.1%
11554463 3
 
< 0.1%

kingdomKey
Real number (ℝ)

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:12.953173image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum584201
Variance0
MonotonicityIncreasing
2025-01-07T10:49:12.994809image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1 584201
100.0%
ValueCountFrequency (%)
1 584201
100.0%
ValueCountFrequency (%)
1 584201
100.0%

phylumKey
Real number (ℝ)

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean44
Minimum44
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:13.034858image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile44
Q144
median44
Q344
95-th percentile44
Maximum44
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean44
Median Absolute Deviation (MAD)0
Skewness0
Sum25704624
Variance0
MonotonicityIncreasing
2025-01-07T10:49:13.078368image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
44 584196
> 99.9%
(Missing) 5
 
< 0.1%
ValueCountFrequency (%)
44 584196
> 99.9%
ValueCountFrequency (%)
44 584196
> 99.9%

classKey
Real number (ℝ)

Distinct5
Distinct (%)< 0.1%
Missing203
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3742694.19
Minimum131
Maximum11592253
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:13.120677image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum131
5-th percentile131
Q1131
median131
Q311592253
95-th percentile11592253
Maximum11592253
Range11592122
Interquartile range (IQR)11592122

Descriptive statistics

Standard deviation5414016.986
Coefficient of variation (CV)1.446556067
Kurtosis-1.42924265
Mean3742694.19
Median Absolute Deviation (MAD)0
Skewness0.7553982039
Sum2.185725921 × 1012
Variance2.931157992 × 1013
MonotonicityNot monotonic
2025-01-07T10:49:13.170187image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
131 395161
67.6%
11592253 169110
28.9%
11418114 18909
 
3.2%
11493978 804
 
0.1%
11569602 14
 
< 0.1%
(Missing) 203
 
< 0.1%
ValueCountFrequency (%)
131 395161
67.6%
11418114 18909
 
3.2%
11493978 804
 
0.1%
11569602 14
 
< 0.1%
11592253 169110
28.9%
ValueCountFrequency (%)
11592253 169110
28.9%
11569602 14
 
< 0.1%
11493978 804
 
0.1%
11418114 18909
 
3.2%
131 395161
67.6%

orderKey
Real number (ℝ)

Missing  Skewed 

Distinct3
Distinct (%)< 0.1%
Missing189040
Missing (%)32.4%
Infinite0
Infinite (%)0.0%
Mean952.3667164
Minimum775
Maximum953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:13.213497image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum775
5-th percentile952
Q1952
median953
Q3953
95-th percentile953
Maximum953
Range178
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.463081714
Coefficient of variation (CV)0.006786337241
Kurtosis744.8272358
Mean952.3667164
Median Absolute Deviation (MAD)0
Skewness-27.24937495
Sum376338184
Variance41.77142525
MonotonicityNot monotonic
2025-01-07T10:49:13.258008image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
953 237129
40.6%
952 157511
27.0%
775 521
 
0.1%
(Missing) 189040
32.4%
ValueCountFrequency (%)
775 521
 
0.1%
952 157511
27.0%
953 237129
40.6%
ValueCountFrequency (%)
953 237129
40.6%
952 157511
27.0%
775 521
 
0.1%

familyKey
Real number (ℝ)

Distinct159
Distinct (%)< 0.1%
Missing587
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean462821.3955
Minimum2237
Maximum11209474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:13.317325image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2237
5-th percentile3540
Q16727
median6748
Q36748
95-th percentile5789478
Maximum11209474
Range11207237
Interquartile range (IQR)21

Descriptive statistics

Standard deviation1795248.866
Coefficient of variation (CV)3.87892367
Kurtosis13.66305505
Mean462821.3955
Median Absolute Deviation (MAD)13
Skewness3.87601716
Sum2.701090459 × 1011
Variance3.222918491 × 1012
MonotonicityNot monotonic
2025-01-07T10:49:13.379692image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6748 221371
37.9%
6735 41566
 
7.1%
6172 38793
 
6.6%
9115 26153
 
4.5%
6727 25125
 
4.3%
6746 20333
 
3.5%
8345926 18373
 
3.1%
5666 17255
 
3.0%
5016 16259
 
2.8%
6739 10435
 
1.8%
Other values (149) 147951
25.3%
ValueCountFrequency (%)
2237 90
 
< 0.1%
2238 1960
0.3%
3075 954
0.2%
3076 594
 
0.1%
3077 207
 
< 0.1%
ValueCountFrequency (%)
11209474 121
< 0.1%
11182941 72
< 0.1%
10874056 106
< 0.1%
10832023 1
 
< 0.1%
10765577 11
 
< 0.1%

genusKey
Real number (ℝ)

Distinct1418
Distinct (%)0.2%
Missing1685
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean3118624.505
Minimum2421432
Maximum11662618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:13.442031image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2421432
5-th percentile2422857
Q12431198
median2431477
Q32454765
95-th percentile8782549
Maximum11662618
Range9241186
Interquartile range (IQR)23567

Descriptive statistics

Standard deviation1898607.856
Coefficient of variation (CV)0.6087965553
Kurtosis5.947772419
Mean3118624.505
Median Absolute Deviation (MAD)4431
Skewness2.719522756
Sum1.816648672 × 1012
Variance3.604711789 × 1012
MonotonicityNot monotonic
2025-01-07T10:49:13.505313image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2431477 168423
28.8%
2431198 35846
 
6.1%
8782549 18373
 
3.1%
2427046 12991
 
2.2%
2424035 9948
 
1.7%
2422857 9476
 
1.6%
2451143 8824
 
1.5%
2463307 8233
 
1.4%
5218343 7667
 
1.3%
2428124 6800
 
1.2%
Other values (1408) 295935
50.7%
ValueCountFrequency (%)
2421432 278
< 0.1%
2421433 134
 
< 0.1%
2421446 360
0.1%
2421575 11
 
< 0.1%
2421577 97
 
< 0.1%
ValueCountFrequency (%)
11662618 414
0.1%
11466920 1
 
< 0.1%
11201690 3
 
< 0.1%
11181753 18
 
< 0.1%
11175467 52
 
< 0.1%

subgenusKey
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

speciesKey
Real number (ℝ)

Missing 

Distinct7286
Distinct (%)1.3%
Missing15011
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean3568930.055
Minimum2421447
Maximum12221705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:13.569825image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2421447
5-th percentile2424120
Q12431231
median2431521
Q32470656
95-th percentile9229667.95
Maximum12221705
Range9800258
Interquartile range (IQR)39425

Descriptive statistics

Standard deviation2279133.542
Coefficient of variation (CV)0.6386041495
Kurtosis2.688249198
Mean3568930.055
Median Absolute Deviation (MAD)4819
Skewness1.969467907
Sum2.031399298 × 1012
Variance5.194449704 × 1012
MonotonicityNot monotonic
2025-01-07T10:49:13.632660image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2431491 75714
 
13.0%
2431539 13092
 
2.2%
2431224 10146
 
1.7%
2431506 9986
 
1.7%
2431516 8012
 
1.4%
2431529 7074
 
1.2%
2431489 6103
 
1.0%
2431484 5929
 
1.0%
2431219 4681
 
0.8%
2431510 4614
 
0.8%
Other values (7276) 423839
72.6%
(Missing) 15011
 
2.6%
ValueCountFrequency (%)
2421447 233
< 0.1%
2421471 42
 
< 0.1%
2421485 2
 
< 0.1%
2421489 3
 
< 0.1%
2421491 23
 
< 0.1%
ValueCountFrequency (%)
12221705 1
 
< 0.1%
11815352 413
0.1%
11804395 1
 
< 0.1%
11554463 3
 
< 0.1%
11528555 1
 
< 0.1%

species
Text

Missing 

Distinct7285
Distinct (%)1.3%
Missing15011
Missing (%)2.6%
Memory size4.5 MiB
2025-01-07T10:49:13.805178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length34
Median length31
Mean length19.39421459
Min length9

Characters and Unicode

Total characters11038993
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1233 ?
Unique (%)0.2%

Sample

1st rowCarlia bicarinata
2nd rowPlethodon montanus
3rd rowEnhydris enhydris
4th rowGehyra mutilata
5th rowAnolis richardii
ValueCountFrequency (%)
plethodon 165820
 
14.6%
cinereus 77201
 
6.8%
desmognathus 34836
 
3.1%
anolis 18232
 
1.6%
glutinosus 13098
 
1.2%
lithobates 12881
 
1.1%
fuscus 10914
 
1.0%
montanus 10391
 
0.9%
eleutherodactylus 9909
 
0.9%
anaxyrus 9456
 
0.8%
Other values (6398) 775642
68.1%
2025-01-07T10:49:14.048907image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 936730
 
8.5%
o 931837
 
8.4%
s 908046
 
8.2%
a 828057
 
7.5%
i 769871
 
7.0%
n 699609
 
6.3%
t 680178
 
6.2%
l 614875
 
5.6%
r 614619
 
5.6%
u 607807
 
5.5%
Other values (44) 3447364
31.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11038993
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 936730
 
8.5%
o 931837
 
8.4%
s 908046
 
8.2%
a 828057
 
7.5%
i 769871
 
7.0%
n 699609
 
6.3%
t 680178
 
6.2%
l 614875
 
5.6%
r 614619
 
5.6%
u 607807
 
5.5%
Other values (44) 3447364
31.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11038993
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 936730
 
8.5%
o 931837
 
8.4%
s 908046
 
8.2%
a 828057
 
7.5%
i 769871
 
7.0%
n 699609
 
6.3%
t 680178
 
6.2%
l 614875
 
5.6%
r 614619
 
5.6%
u 607807
 
5.5%
Other values (44) 3447364
31.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11038993
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 936730
 
8.5%
o 931837
 
8.4%
s 908046
 
8.2%
a 828057
 
7.5%
i 769871
 
7.0%
n 699609
 
6.3%
t 680178
 
6.2%
l 614875
 
5.6%
r 614619
 
5.6%
u 607807
 
5.5%
Other values (44) 3447364
31.2%
Distinct8475
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:14.254033image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length182
Median length112
Mean length35.64721046
Min length5

Characters and Unicode

Total characters20825136
Distinct characters88
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1520 ?
Unique (%)0.3%

Sample

1st rowCarlia bicarinata (Macleay, 1877)
2nd rowPlethodon montanus Highton & Peabody, 2000
3rd rowEnhydris enhydris (Schneider, 1799)
4th rowGehyra mutilata (Wiegmann, 1834)
5th rowAnolis richardii Duméril & Bibron, 1837
ValueCountFrequency (%)
plethodon 168423
 
6.7%
green 95577
 
3.8%
1818 93564
 
3.7%
82003
 
3.3%
cinereus 77201
 
3.1%
desmognathus 35846
 
1.4%
cope 33460
 
1.3%
duméril 27066
 
1.1%
linnaeus 26934
 
1.1%
bibron 23993
 
1.0%
Other values (8473) 1852441
73.6%
2025-01-07T10:49:14.534584image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1932307
 
9.3%
e 1568353
 
7.5%
o 1194544
 
5.7%
n 1166456
 
5.6%
a 1137420
 
5.5%
i 1101341
 
5.3%
s 1056757
 
5.1%
r 1050847
 
5.0%
t 855218
 
4.1%
l 825579
 
4.0%
Other values (78) 8936314
42.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20825136
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1932307
 
9.3%
e 1568353
 
7.5%
o 1194544
 
5.7%
n 1166456
 
5.6%
a 1137420
 
5.5%
i 1101341
 
5.3%
s 1056757
 
5.1%
r 1050847
 
5.0%
t 855218
 
4.1%
l 825579
 
4.0%
Other values (78) 8936314
42.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20825136
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1932307
 
9.3%
e 1568353
 
7.5%
o 1194544
 
5.7%
n 1166456
 
5.6%
a 1137420
 
5.5%
i 1101341
 
5.3%
s 1056757
 
5.1%
r 1050847
 
5.0%
t 855218
 
4.1%
l 825579
 
4.0%
Other values (78) 8936314
42.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20825136
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1932307
 
9.3%
e 1568353
 
7.5%
o 1194544
 
5.7%
n 1166456
 
5.6%
a 1137420
 
5.5%
i 1101341
 
5.3%
s 1056757
 
5.1%
r 1050847
 
5.0%
t 855218
 
4.1%
l 825579
 
4.0%
Other values (78) 8936314
42.9%
Distinct9530
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:14.746537image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length62
Median length56
Mean length19.84556343
Min length4

Characters and Unicode

Total characters11593798
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1890 ?
Unique (%)0.3%

Sample

1st rowCarlia bicarinata
2nd rowPlethodon montanus
3rd rowEnhydris enhydris
4th rowGehyra mutilata
5th rowAnolis richardii
ValueCountFrequency (%)
plethodon 168423
 
14.0%
cinereus 75774
 
6.3%
desmognathus 35846
 
3.0%
anolis 18352
 
1.5%
glutinosus 13372
 
1.1%
lithobates 12991
 
1.1%
fuscus 11321
 
0.9%
montanus 10417
 
0.9%
eleutherodactylus 9959
 
0.8%
anaxyrus 9474
 
0.8%
Other values (7195) 837184
69.6%
2025-01-07T10:49:15.023084image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 976778
 
8.4%
o 954528
 
8.2%
s 947788
 
8.2%
a 896948
 
7.7%
i 821046
 
7.1%
n 729826
 
6.3%
t 711935
 
6.1%
l 642687
 
5.5%
u 635392
 
5.5%
r 633897
 
5.5%
Other values (49) 3642973
31.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11593798
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 976778
 
8.4%
o 954528
 
8.2%
s 947788
 
8.2%
a 896948
 
7.7%
i 821046
 
7.1%
n 729826
 
6.3%
t 711935
 
6.1%
l 642687
 
5.5%
u 635392
 
5.5%
r 633897
 
5.5%
Other values (49) 3642973
31.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11593798
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 976778
 
8.4%
o 954528
 
8.2%
s 947788
 
8.2%
a 896948
 
7.7%
i 821046
 
7.1%
n 729826
 
6.3%
t 711935
 
6.1%
l 642687
 
5.5%
u 635392
 
5.5%
r 633897
 
5.5%
Other values (49) 3642973
31.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11593798
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 976778
 
8.4%
o 954528
 
8.2%
s 947788
 
8.2%
a 896948
 
7.7%
i 821046
 
7.1%
n 729826
 
6.3%
t 711935
 
6.1%
l 642687
 
5.5%
u 635392
 
5.5%
r 633897
 
5.5%
Other values (49) 3642973
31.4%

typifiedName
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

protocol
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:15.077177image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1752603
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEML
2nd rowEML
3rd rowEML
4th rowEML
5th rowEML
ValueCountFrequency (%)
eml 584201
100.0%
2025-01-07T10:49:15.166859image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 584201
33.3%
M 584201
33.3%
L 584201
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1752603
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 584201
33.3%
M 584201
33.3%
L 584201
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1752603
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 584201
33.3%
M 584201
33.3%
L 584201
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1752603
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 584201
33.3%
M 584201
33.3%
L 584201
33.3%
Distinct186736
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:15.307352image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99567957
Min length20

Characters and Unicode

Total characters14018300
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40383 ?
Unique (%)6.9%

Sample

1st row2024-12-02T13:56:06.739Z
2nd row2024-12-02T13:56:08.224Z
3rd row2024-12-02T13:55:56.801Z
4th row2024-12-02T13:59:51.499Z
5th row2024-12-02T13:58:04.592Z
ValueCountFrequency (%)
2024-12-02t13:57:45.601z 17
 
< 0.1%
2024-12-02t13:57:51.135z 16
 
< 0.1%
2024-12-02t13:57:54.221z 16
 
< 0.1%
2024-12-02t13:57:23.249z 16
 
< 0.1%
2024-12-02t13:57:52.847z 16
 
< 0.1%
2024-12-02t13:57:53.169z 15
 
< 0.1%
2024-12-02t13:58:01.663z 15
 
< 0.1%
2024-12-02t13:56:52.538z 15
 
< 0.1%
2024-12-02t13:57:22.814z 15
 
< 0.1%
2024-12-02t13:57:12.319z 15
 
< 0.1%
Other values (186726) 584045
> 99.9%
2025-01-07T10:49:15.538641image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2668002
19.0%
0 1480784
10.6%
1 1472907
10.5%
- 1168402
8.3%
: 1168402
8.3%
4 939301
 
6.7%
5 927875
 
6.6%
3 926225
 
6.6%
T 584201
 
4.2%
Z 584201
 
4.2%
Other values (5) 2098000
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14018300
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2668002
19.0%
0 1480784
10.6%
1 1472907
10.5%
- 1168402
8.3%
: 1168402
8.3%
4 939301
 
6.7%
5 927875
 
6.6%
3 926225
 
6.6%
T 584201
 
4.2%
Z 584201
 
4.2%
Other values (5) 2098000
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14018300
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2668002
19.0%
0 1480784
10.6%
1 1472907
10.5%
- 1168402
8.3%
: 1168402
8.3%
4 939301
 
6.7%
5 927875
 
6.6%
3 926225
 
6.6%
T 584201
 
4.2%
Z 584201
 
4.2%
Other values (5) 2098000
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14018300
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2668002
19.0%
0 1480784
10.6%
1 1472907
10.5%
- 1168402
8.3%
: 1168402
8.3%
4 939301
 
6.7%
5 927875
 
6.6%
3 926225
 
6.6%
T 584201
 
4.2%
Z 584201
 
4.2%
Other values (5) 2098000
15.0%

lastCrawled
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:15.599828image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters14020824
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-12-02T11:48:23.416Z
2nd row2024-12-02T11:48:23.416Z
3rd row2024-12-02T11:48:23.416Z
4th row2024-12-02T11:48:23.416Z
5th row2024-12-02T11:48:23.416Z
ValueCountFrequency (%)
2024-12-02t11:48:23.416z 584201
100.0%
2025-01-07T10:49:15.779332image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2921005
20.8%
1 2336804
16.7%
4 1752603
12.5%
0 1168402
 
8.3%
- 1168402
 
8.3%
: 1168402
 
8.3%
T 584201
 
4.2%
8 584201
 
4.2%
3 584201
 
4.2%
. 584201
 
4.2%
Other values (2) 1168402
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14020824
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2921005
20.8%
1 2336804
16.7%
4 1752603
12.5%
0 1168402
 
8.3%
- 1168402
 
8.3%
: 1168402
 
8.3%
T 584201
 
4.2%
8 584201
 
4.2%
3 584201
 
4.2%
. 584201
 
4.2%
Other values (2) 1168402
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14020824
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2921005
20.8%
1 2336804
16.7%
4 1752603
12.5%
0 1168402
 
8.3%
- 1168402
 
8.3%
: 1168402
 
8.3%
T 584201
 
4.2%
8 584201
 
4.2%
3 584201
 
4.2%
. 584201
 
4.2%
Other values (2) 1168402
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14020824
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2921005
20.8%
1 2336804
16.7%
4 1752603
12.5%
0 1168402
 
8.3%
- 1168402
 
8.3%
: 1168402
 
8.3%
T 584201
 
4.2%
8 584201
 
4.2%
3 584201
 
4.2%
. 584201
 
4.2%
Other values (2) 1168402
 
8.3%

repatriated
Boolean

Missing 

Distinct2
Distinct (%)< 0.1%
Missing10596
Missing (%)1.8%
Memory size4.5 MiB
False
334216 
True
239389 
(Missing)
 
10596
ValueCountFrequency (%)
False 334216
57.2%
True 239389
41.0%
(Missing) 10596
 
1.8%
2025-01-07T10:49:15.830371image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

relativeOrganismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

projectId
Unsupported

Missing  Rejected  Unsupported 

Missing584201
Missing (%)100.0%
Memory size4.5 MiB

isSequenced
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size570.6 KiB
False
583480 
True
 
721
ValueCountFrequency (%)
False 583480
99.9%
True 721
 
0.1%
2025-01-07T10:49:15.867878image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

gbifRegion
Text

Missing 

Distinct6
Distinct (%)< 0.1%
Missing11409
Missing (%)2.0%
Memory size4.5 MiB
2025-01-07T10:49:15.901211image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length11.80906158
Min length4

Characters and Unicode

Total characters6764136
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOCEANIA
2nd rowNORTH_AMERICA
3rd rowOCEANIA
4th rowLATIN_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 335375
58.6%
latin_america 147208
25.7%
asia 39442
 
6.9%
oceania 28187
 
4.9%
africa 19937
 
3.5%
europe 2643
 
0.5%
2025-01-07T10:49:16.001724image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1287506
19.0%
R 840538
12.4%
I 717357
10.6%
C 530707
7.8%
E 516056
7.6%
N 510770
 
7.6%
M 482583
 
7.1%
T 482583
 
7.1%
_ 482583
 
7.1%
O 366205
 
5.4%
Other values (6) 547248
8.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6764136
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1287506
19.0%
R 840538
12.4%
I 717357
10.6%
C 530707
7.8%
E 516056
7.6%
N 510770
 
7.6%
M 482583
 
7.1%
T 482583
 
7.1%
_ 482583
 
7.1%
O 366205
 
5.4%
Other values (6) 547248
8.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6764136
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1287506
19.0%
R 840538
12.4%
I 717357
10.6%
C 530707
7.8%
E 516056
7.6%
N 510770
 
7.6%
M 482583
 
7.1%
T 482583
 
7.1%
_ 482583
 
7.1%
O 366205
 
5.4%
Other values (6) 547248
8.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6764136
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1287506
19.0%
R 840538
12.4%
I 717357
10.6%
C 530707
7.8%
E 516056
7.6%
N 510770
 
7.6%
M 482583
 
7.1%
T 482583
 
7.1%
_ 482583
 
7.1%
O 366205
 
5.4%
Other values (6) 547248
8.1%

publishedByGbifRegion
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:49:16.049727image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters7594613
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 584201
100.0%
2025-01-07T10:49:16.146620image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 1168402
15.4%
A 1168402
15.4%
N 584201
7.7%
O 584201
7.7%
T 584201
7.7%
H 584201
7.7%
_ 584201
7.7%
M 584201
7.7%
E 584201
7.7%
I 584201
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7594613
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
R 1168402
15.4%
A 1168402
15.4%
N 584201
7.7%
O 584201
7.7%
T 584201
7.7%
H 584201
7.7%
_ 584201
7.7%
M 584201
7.7%
E 584201
7.7%
I 584201
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7594613
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
R 1168402
15.4%
A 1168402
15.4%
N 584201
7.7%
O 584201
7.7%
T 584201
7.7%
H 584201
7.7%
_ 584201
7.7%
M 584201
7.7%
E 584201
7.7%
I 584201
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7594613
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
R 1168402
15.4%
A 1168402
15.4%
N 584201
7.7%
O 584201
7.7%
T 584201
7.7%
H 584201
7.7%
_ 584201
7.7%
M 584201
7.7%
E 584201
7.7%
I 584201
7.7%

level0Gid
Text

Missing 

Distinct175
Distinct (%)< 0.1%
Missing173676
Missing (%)29.7%
Memory size4.5 MiB
2025-01-07T10:49:16.289485image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1231575
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st rowPNG
2nd rowUSA
3rd rowGRD
4th rowUSA
5th rowUSA
ValueCountFrequency (%)
usa 282827
68.9%
ecu 14871
 
3.6%
bra 13519
 
3.3%
per 12508
 
3.0%
hnd 10032
 
2.4%
mex 4961
 
1.2%
dom 4618
 
1.1%
cub 3855
 
0.9%
png 3606
 
0.9%
hti 3483
 
0.8%
Other values (165) 56245
 
13.7%
2025-01-07T10:49:16.481360image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 308853
25.1%
A 306743
24.9%
S 286617
23.3%
R 40442
 
3.3%
E 40339
 
3.3%
P 28015
 
2.3%
N 27326
 
2.2%
C 26870
 
2.2%
M 25313
 
2.1%
B 21622
 
1.8%
Other values (18) 119435
 
9.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1231575
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 308853
25.1%
A 306743
24.9%
S 286617
23.3%
R 40442
 
3.3%
E 40339
 
3.3%
P 28015
 
2.3%
N 27326
 
2.2%
C 26870
 
2.2%
M 25313
 
2.1%
B 21622
 
1.8%
Other values (18) 119435
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1231575
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 308853
25.1%
A 306743
24.9%
S 286617
23.3%
R 40442
 
3.3%
E 40339
 
3.3%
P 28015
 
2.3%
N 27326
 
2.2%
C 26870
 
2.2%
M 25313
 
2.1%
B 21622
 
1.8%
Other values (18) 119435
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1231575
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 308853
25.1%
A 306743
24.9%
S 286617
23.3%
R 40442
 
3.3%
E 40339
 
3.3%
P 28015
 
2.3%
N 27326
 
2.2%
C 26870
 
2.2%
M 25313
 
2.1%
B 21622
 
1.8%
Other values (18) 119435
 
9.7%

level0Name
Text

Missing 

Distinct175
Distinct (%)< 0.1%
Missing173676
Missing (%)29.7%
Memory size4.5 MiB
2025-01-07T10:49:16.670054image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length13
Mean length11.47883564
Min length4

Characters and Unicode

Total characters4712349
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st rowPapua New Guinea
2nd rowUnited States
3rd rowGrenada
4th rowUnited States
5th rowUnited States
ValueCountFrequency (%)
united 283460
38.9%
states 283455
38.9%
ecuador 14871
 
2.0%
brazil 13519
 
1.9%
peru 12508
 
1.7%
honduras 10032
 
1.4%
republic 5833
 
0.8%
méxico 4961
 
0.7%
dominican 4618
 
0.6%
guinea 3935
 
0.5%
Other values (203) 92017
 
12.6%
2025-01-07T10:49:16.917034image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 869782
18.5%
e 617316
13.1%
a 436923
9.3%
i 361412
7.7%
n 346814
 
7.4%
d 321822
 
6.8%
318684
 
6.8%
s 308278
 
6.5%
S 286866
 
6.1%
U 283929
 
6.0%
Other values (48) 560523
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4712349
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 869782
18.5%
e 617316
13.1%
a 436923
9.3%
i 361412
7.7%
n 346814
 
7.4%
d 321822
 
6.8%
318684
 
6.8%
s 308278
 
6.5%
S 286866
 
6.1%
U 283929
 
6.0%
Other values (48) 560523
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4712349
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 869782
18.5%
e 617316
13.1%
a 436923
9.3%
i 361412
7.7%
n 346814
 
7.4%
d 321822
 
6.8%
318684
 
6.8%
s 308278
 
6.5%
S 286866
 
6.1%
U 283929
 
6.0%
Other values (48) 560523
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4712349
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 869782
18.5%
e 617316
13.1%
a 436923
9.3%
i 361412
7.7%
n 346814
 
7.4%
d 321822
 
6.8%
318684
 
6.8%
s 308278
 
6.5%
S 286866
 
6.1%
U 283929
 
6.0%
Other values (48) 560523
11.9%

level1Gid
Text

Missing 

Distinct1192
Distinct (%)0.3%
Missing174349
Missing (%)29.8%
Memory size4.5 MiB
2025-01-07T10:49:17.122170image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.801640592
Min length6

Characters and Unicode

Total characters3197518
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)< 0.1%

Sample

1st rowPNG.2_1
2nd rowUSA.34_1
3rd rowGRD.4_1
4th rowUSA.47_1
5th rowUSA.29_1
ValueCountFrequency (%)
usa.47_1 68346
 
16.7%
usa.34_1 51010
 
12.4%
usa.21_1 30907
 
7.5%
usa.39_1 18483
 
4.5%
usa.49_1 17227
 
4.2%
usa.43_1 10691
 
2.6%
usa.5_1 8858
 
2.2%
usa.11_1 8403
 
2.1%
usa.10_1 7784
 
1.9%
usa.37_1 5139
 
1.3%
Other values (1182) 183004
44.7%
2025-01-07T10:49:17.389046image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 548162
17.1%
_ 409852
12.8%
. 409646
12.8%
U 308853
9.7%
A 306694
9.6%
S 286615
9.0%
4 178904
 
5.6%
3 121201
 
3.8%
7 85072
 
2.7%
2 75286
 
2.4%
Other values (28) 467233
14.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3197518
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 548162
17.1%
_ 409852
12.8%
. 409646
12.8%
U 308853
9.7%
A 306694
9.6%
S 286615
9.0%
4 178904
 
5.6%
3 121201
 
3.8%
7 85072
 
2.7%
2 75286
 
2.4%
Other values (28) 467233
14.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3197518
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 548162
17.1%
_ 409852
12.8%
. 409646
12.8%
U 308853
9.7%
A 306694
9.6%
S 286615
9.0%
4 178904
 
5.6%
3 121201
 
3.8%
7 85072
 
2.7%
2 75286
 
2.4%
Other values (28) 467233
14.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3197518
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 548162
17.1%
_ 409852
12.8%
. 409646
12.8%
U 308853
9.7%
A 306694
9.6%
S 286615
9.0%
4 178904
 
5.6%
3 121201
 
3.8%
7 85072
 
2.7%
2 75286
 
2.4%
Other values (28) 467233
14.6%

level1Name
Text

Missing 

Distinct1147
Distinct (%)0.3%
Missing174349
Missing (%)29.8%
Memory size4.5 MiB
2025-01-07T10:49:17.585670image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length30
Mean length9.58385466
Min length3

Characters and Unicode

Total characters3927962
Distinct characters99
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)< 0.1%

Sample

1st rowCentral
2nd rowNorth Carolina
3rd rowSaint George
4th rowVirginia
5th rowNevada
ValueCountFrequency (%)
virginia 85573
 
15.6%
carolina 55602
 
10.1%
north 51399
 
9.3%
maryland 30907
 
5.6%
pennsylvania 18483
 
3.4%
west 17320
 
3.1%
tennessee 10691
 
1.9%
california 9457
 
1.7%
georgia 8403
 
1.5%
de 7912
 
1.4%
Other values (1285) 254513
46.3%
2025-01-07T10:49:17.853730image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 585330
14.9%
i 477589
12.2%
n 369556
 
9.4%
r 331611
 
8.4%
o 265471
 
6.8%
l 174911
 
4.5%
e 169093
 
4.3%
s 148236
 
3.8%
140408
 
3.6%
t 129070
 
3.3%
Other values (89) 1136687
28.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3927962
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 585330
14.9%
i 477589
12.2%
n 369556
 
9.4%
r 331611
 
8.4%
o 265471
 
6.8%
l 174911
 
4.5%
e 169093
 
4.3%
s 148236
 
3.8%
140408
 
3.6%
t 129070
 
3.3%
Other values (89) 1136687
28.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3927962
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 585330
14.9%
i 477589
12.2%
n 369556
 
9.4%
r 331611
 
8.4%
o 265471
 
6.8%
l 174911
 
4.5%
e 169093
 
4.3%
s 148236
 
3.8%
140408
 
3.6%
t 129070
 
3.3%
Other values (89) 1136687
28.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3927962
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 585330
14.9%
i 477589
12.2%
n 369556
 
9.4%
r 331611
 
8.4%
o 265471
 
6.8%
l 174911
 
4.5%
e 169093
 
4.3%
s 148236
 
3.8%
140408
 
3.6%
t 129070
 
3.3%
Other values (89) 1136687
28.9%

level2Gid
Text

Missing 

Distinct4973
Distinct (%)1.2%
Missing186113
Missing (%)31.9%
Memory size4.5 MiB
2025-01-07T10:49:18.073103image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.59813157
Min length8

Characters and Unicode

Total characters4218989
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique873 ?
Unique (%)0.2%

Sample

1st rowPNG.2.3_1
2nd rowUSA.34.11_1
3rd rowUSA.47.9_1
4th rowUSA.29.5_1
5th rowBRA.19.34_2
ValueCountFrequency (%)
usa.34.87_1 9937
 
2.5%
usa.47.50_1 7933
 
2.0%
usa.21.10_1 6723
 
1.7%
usa.34.56_1 6344
 
1.6%
usa.34.44_1 5697
 
1.4%
per.1.4_1 4919
 
1.2%
usa.21.16_1 4431
 
1.1%
usa.43.78_1 3919
 
1.0%
usa.49.42_1 3487
 
0.9%
usa.47.53_1 3397
 
0.9%
Other values (4963) 341301
85.7%
2025-01-07T10:49:18.352788image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 795970
18.9%
1 660755
15.7%
_ 398088
9.4%
A 305944
 
7.3%
U 305494
 
7.2%
S 286408
 
6.8%
4 250715
 
5.9%
3 195227
 
4.6%
2 179315
 
4.3%
7 136265
 
3.2%
Other values (28) 704808
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4218989
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 795970
18.9%
1 660755
15.7%
_ 398088
9.4%
A 305944
 
7.3%
U 305494
 
7.2%
S 286408
 
6.8%
4 250715
 
5.9%
3 195227
 
4.6%
2 179315
 
4.3%
7 136265
 
3.2%
Other values (28) 704808
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4218989
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 795970
18.9%
1 660755
15.7%
_ 398088
9.4%
A 305944
 
7.3%
U 305494
 
7.2%
S 286408
 
6.8%
4 250715
 
5.9%
3 195227
 
4.6%
2 179315
 
4.3%
7 136265
 
3.2%
Other values (28) 704808
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4218989
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 795970
18.9%
1 660755
15.7%
_ 398088
9.4%
A 305944
 
7.3%
U 305494
 
7.2%
S 286408
 
6.8%
4 250715
 
5.9%
3 195227
 
4.6%
2 179315
 
4.3%
7 136265
 
3.2%
Other values (28) 704808
16.7%

level2Name
Text

Missing 

Distinct4138
Distinct (%)1.0%
Missing186171
Missing (%)31.9%
Memory size4.5 MiB
2025-01-07T10:49:18.556370image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length28
Mean length8.217365525
Min length2

Characters and Unicode

Total characters3270758
Distinct characters109
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique730 ?
Unique (%)0.2%

Sample

1st rowKairuku-Hiri
2nd rowBuncombe
3rd rowAugusta
4th rowElko
5th rowItatiaia
ValueCountFrequency (%)
swain 9937
 
2.0%
giles 7933
 
1.6%
frederick 7093
 
1.5%
macon 6483
 
1.3%
madison 6402
 
1.3%
de 6373
 
1.3%
haywood 5697
 
1.2%
la 5624
 
1.1%
san 5466
 
1.1%
prince 5405
 
1.1%
Other values (4402) 422665
86.4%
2025-01-07T10:49:18.828733image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 366588
 
11.2%
e 273177
 
8.4%
n 252799
 
7.7%
o 249950
 
7.6%
r 207979
 
6.4%
i 190585
 
5.8%
l 143560
 
4.4%
s 133215
 
4.1%
t 117958
 
3.6%
u 95083
 
2.9%
Other values (99) 1239864
37.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3270758
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 366588
 
11.2%
e 273177
 
8.4%
n 252799
 
7.7%
o 249950
 
7.6%
r 207979
 
6.4%
i 190585
 
5.8%
l 143560
 
4.4%
s 133215
 
4.1%
t 117958
 
3.6%
u 95083
 
2.9%
Other values (99) 1239864
37.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3270758
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 366588
 
11.2%
e 273177
 
8.4%
n 252799
 
7.7%
o 249950
 
7.6%
r 207979
 
6.4%
i 190585
 
5.8%
l 143560
 
4.4%
s 133215
 
4.1%
t 117958
 
3.6%
u 95083
 
2.9%
Other values (99) 1239864
37.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3270758
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 366588
 
11.2%
e 273177
 
8.4%
n 252799
 
7.7%
o 249950
 
7.6%
r 207979
 
6.4%
i 190585
 
5.8%
l 143560
 
4.4%
s 133215
 
4.1%
t 117958
 
3.6%
u 95083
 
2.9%
Other values (99) 1239864
37.9%

level3Gid
Text

Missing 

Distinct1518
Distinct (%)2.9%
Missing532468
Missing (%)91.1%
Memory size4.5 MiB
2025-01-07T10:49:19.043263image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.70438598
Min length11

Characters and Unicode

Total characters605503
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique345 ?
Unique (%)0.7%

Sample

1st rowECU.18.4.5_1
2nd rowBOL.6.5.3_2
3rd rowPER.18.3.4_1
4th rowECU.18.4.2_1
5th rowPER.1.4.3_1
ValueCountFrequency (%)
per.1.4.3_1 3333
 
6.4%
per.18.3.4_1 1833
 
3.5%
per.1.4.1_1 1584
 
3.1%
per.8.9.1_1 1099
 
2.1%
per.18.1.1_1 862
 
1.7%
cri.3.3.4_1 850
 
1.6%
pan.3.3.1_1 816
 
1.6%
per.8.11.5_1 790
 
1.5%
ecu.21.2.7_1 708
 
1.4%
mdg.6.2.3_1 683
 
1.3%
Other values (1508) 39175
75.7%
2025-01-07T10:49:19.313216image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 155199
25.6%
1 109811
18.1%
_ 51733
 
8.5%
E 29941
 
4.9%
2 26345
 
4.4%
3 23876
 
3.9%
4 23543
 
3.9%
R 20134
 
3.3%
C 19996
 
3.3%
U 14987
 
2.5%
Other values (24) 129938
21.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 605503
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 155199
25.6%
1 109811
18.1%
_ 51733
 
8.5%
E 29941
 
4.9%
2 26345
 
4.4%
3 23876
 
3.9%
4 23543
 
3.9%
R 20134
 
3.3%
C 19996
 
3.3%
U 14987
 
2.5%
Other values (24) 129938
21.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 605503
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 155199
25.6%
1 109811
18.1%
_ 51733
 
8.5%
E 29941
 
4.9%
2 26345
 
4.4%
3 23876
 
3.9%
4 23543
 
3.9%
R 20134
 
3.3%
C 19996
 
3.3%
U 14987
 
2.5%
Other values (24) 129938
21.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 605503
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 155199
25.6%
1 109811
18.1%
_ 51733
 
8.5%
E 29941
 
4.9%
2 26345
 
4.4%
3 23876
 
3.9%
4 23543
 
3.9%
R 20134
 
3.3%
C 19996
 
3.3%
U 14987
 
2.5%
Other values (24) 129938
21.5%

level3Name
Text

Missing 

Distinct1463
Distinct (%)2.8%
Missing532843
Missing (%)91.2%
Memory size4.5 MiB
2025-01-07T10:49:19.517794image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length28
Mean length10.63014525
Min length3

Characters and Unicode

Total characters545943
Distinct characters96
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique325 ?
Unique (%)0.6%

Sample

1st rowMontalvo (Andoas)
2nd rowCobija
3rd rowTambopata
4th rowDiez De Agosto
5th rowRio Santiago
ValueCountFrequency (%)
de 3839
 
4.4%
rio 3728
 
4.3%
santiago 3466
 
4.0%
el 3141
 
3.6%
san 1843
 
2.1%
tambopata 1833
 
2.1%
cenepa 1584
 
1.8%
santa 1305
 
1.5%
cab 1203
 
1.4%
en 1101
 
1.3%
Other values (1721) 64179
73.6%
2025-01-07T10:49:19.780386image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 83102
15.2%
o 46946
 
8.6%
35864
 
6.6%
n 35831
 
6.6%
i 30929
 
5.7%
e 29861
 
5.5%
r 26273
 
4.8%
t 20664
 
3.8%
l 19562
 
3.6%
u 17432
 
3.2%
Other values (86) 199479
36.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 545943
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 83102
15.2%
o 46946
 
8.6%
35864
 
6.6%
n 35831
 
6.6%
i 30929
 
5.7%
e 29861
 
5.5%
r 26273
 
4.8%
t 20664
 
3.8%
l 19562
 
3.6%
u 17432
 
3.2%
Other values (86) 199479
36.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 545943
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 83102
15.2%
o 46946
 
8.6%
35864
 
6.6%
n 35831
 
6.6%
i 30929
 
5.7%
e 29861
 
5.5%
r 26273
 
4.8%
t 20664
 
3.8%
l 19562
 
3.6%
u 17432
 
3.2%
Other values (86) 199479
36.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 545943
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 83102
15.2%
o 46946
 
8.6%
35864
 
6.6%
n 35831
 
6.6%
i 30929
 
5.7%
e 29861
 
5.5%
r 26273
 
4.8%
t 20664
 
3.8%
l 19562
 
3.6%
u 17432
 
3.2%
Other values (86) 199479
36.5%

iucnRedListCategory
Text

Missing 

Distinct9
Distinct (%)< 0.1%
Missing23468
Missing (%)4.0%
Memory size4.5 MiB
2025-01-07T10:49:19.836385image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1121466
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowLC
2nd rowLC
3rd rowLC
4th rowLC
5th rowLC
ValueCountFrequency (%)
lc 459843
82.0%
ne 34497
 
6.2%
nt 23131
 
4.1%
vu 21629
 
3.9%
en 10407
 
1.9%
cr 6915
 
1.2%
dd 4133
 
0.7%
ex 177
 
< 0.1%
ew 1
 
< 0.1%
2025-01-07T10:49:19.930365image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 466758
41.6%
L 459843
41.0%
N 68035
 
6.1%
E 45082
 
4.0%
T 23131
 
2.1%
V 21629
 
1.9%
U 21629
 
1.9%
D 8266
 
0.7%
R 6915
 
0.6%
X 177
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1121466
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 466758
41.6%
L 459843
41.0%
N 68035
 
6.1%
E 45082
 
4.0%
T 23131
 
2.1%
V 21629
 
1.9%
U 21629
 
1.9%
D 8266
 
0.7%
R 6915
 
0.6%
X 177
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1121466
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 466758
41.6%
L 459843
41.0%
N 68035
 
6.1%
E 45082
 
4.0%
T 23131
 
2.1%
V 21629
 
1.9%
U 21629
 
1.9%
D 8266
 
0.7%
R 6915
 
0.6%
X 177
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1121466
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 466758
41.6%
L 459843
41.0%
N 68035
 
6.1%
E 45082
 
4.0%
T 23131
 
2.1%
V 21629
 
1.9%
U 21629
 
1.9%
D 8266
 
0.7%
R 6915
 
0.6%
X 177
 
< 0.1%